Public Opinion Survey on the Accuracy of
Weather Forecasts in Hong Kong 2010
- Report -
Prepared for
Prepared by
May 2010
Table of Contents
1 Executive Summary ............................................................................................................ 1
2 Background ......................................................................................................................... 8
3 Objectives ............................................................................................................................ 9
4 Methodology ...................................................................................................................... 10
4.1 Survey Coverage ....................................................................................................... 10
4.2 Research Design ........................................................................................................ 10
4.3 Questionnaire Design ................................................................................................. 11
4.4 Statistical Analysis and Presentation of Survey Results ............................................. 11
5 Detailed Findings .............................................................................................................. 12
5.1 Demographic Profiles of Respondents ....................................................................... 12
5.2 Degree of Concern about Weather Information .......................................................... 13
5.3 Channels to Access Weather Information .................................................................. 13
5.3.1 Popularity of channels to access weather information ............................................................ 13
5.4 Opinions towards the Accuracy of Weather Forecasts over the Past Several Months 16
5.4.1 Overall accuracy level of weather forecasts.............................................................................. 16
5.4.2 Percentage of accurate weather forecasts ................................................................................ 17
5.4.3 Accuracy level of different aspects of weather forecasts ........................................................ 18
5.5 Overall Satisfaction with the Hong Kong Observatory’s Services over the Past Several
Months ....................................................................................................................... 20
5.6 Accuracy Level when Compared to 3 or 4 Years Ago ................................................. 21
5.6.1 Comparison: Accuracy Level of Current Weather Forecasts .................................................. 21
5.6.2 Comparison: Accuracy Level of Current Tropical Cyclone Warning Services ...................... 22
Appendix I: Questionnaire ....................................................................................................... 23
Appendix II: Charts ................................................................................................................... 30
Appendix III: Frequency Tables of Survey Findings .............................................................. 40
Appendix IV: Survey Data Analysis (Cross Tabulation and Statistical Test Results) .......... 48
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
1 May 2010
1 Executive Summary
Introduction
The objective of this survey is to gauge the public’s opinions on the accuracy of weather
forecasts and warnings issued by Hong Kong Observatory (HKO). Specifically, respondents
were invited to express views on the accuracy of weather forecasts based on different
aspects, performance of the HKO over a medium to longer term, and possible channels to
access weather information.
Infogroup|ORC was invited and commissioned by the HKO to conduct two waves of survey
in April and October 2010.
The findings of the first wave of this public opinion survey is summarized in this report; a
total of 1 008 respondents within a systematically selected random sample were
successfully enumerated during the fieldwork period from 16th April to 30th April 2010,
constituting a response rate of 76.29%.
Overview of the Fieldwork Process
Questionnaire Design
In early April, Infogroup|ORC has prepared both the Chinese and English questionnaire
based on the requirements specified by HKO to be pilot tested.
Pilot Survey
The pilot test was conducted on 8 April 2010 to test for the feasibility of the questionnaire
before the commencement of the main fieldwork. Consequently, 30 interviews were
successfully conducted in the pilot test, with interviewing time in the range of 5 to 7 minutes.
No problematic area was identified during the pilot test, and the original questionnaire was
implemented in the main survey as approved by the HKO.
All interviews in the pilot test were not included in the main survey.
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
2 May 2010
Main Survey
Before the main fieldwork was executed, a thorough briefing session was held on 16 April
2010 with enumerators and field work supervisor, in full consultation with HKO staff, to
address the requirements of the survey, principles of confidentiality, and to clarify any
misconception on common meteorological terminologies.
As detailed in the briefing session, a systematic random sampling method was deployed for
this survey. A random sample of households was systematically selected from the
telephone database maintained by Infogroup|ORC.
Using this method, each household in the population has a known and equal probability of
selection.
Once the household was selected and contacted, Kish Grid selection method was
adopted for the selection of the target respondent. In order to ensure the findings of this
survey are representative, only one interview (whether successful or not) has been
conducted in each sampled household.
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
3 May 2010
Summary of Survey Findings
Profile of Users
Of the 1 008 respondents interviewed, 54.5% of which were female; 45.5% were males.
The majority of the respondents were of age 40 – 59 (45.2%) and 20 – 39 (39.5%); the
youth (aged 15 – 19) and the elderly (aged 60 – 64) respondents accounted for 10.4% and
4.9%, respectively.
Analyzed by educational attainment, the proportions of respondents with tertiary or above
education level, secondary to matriculation education level, primary of below education
level were 28.5%, 59.7% and 11.4% respectively.
53.0% of respondents are engaged in full-time employment, just over 10% of the
respondents were unemployed (4.1%) or retired (6.5%), whilst more than 30% of the
respondents were homemakers (19.5%) and students (15.7%). 1.2% of respondents
refused to comment on their employment status.
(Ref.: Question 17 – 19)
Degree of concern about Weather information
The majority of respondents (99.8%) indicated that they usually read, watch or listen to
weather reports, suggesting that the general public is well aware of the weather information
available to them.
(Ref.: Question 1)
Channels to Access Weather Information
Of the channels to access weather information, most respondents (70.1%) obtain weather
information through television, as the primary channel, with the radio (25.5%) as the most
popular alternative channel.
In general, there was an increase in the use of the internet as a mean to access weather
information. More and more respondents (7.4%) were using the HKO's web site as the
primary channel to obtain weather information (against 5.9% in the previous wave).
(Ref.: Question 2 – 7)
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
4 May 2010
Opinions towards the Accuracy of Weather Forecasts
For the perceived accuracy of weather forecasts, 76.2% of respondents considered the
weather forecasts over the past several months to be accurate. Yet some 3% of
respondents asserted the contrary, slightly increased from previous waves (1.2% in April
2009, 1.5% in October 2009).
The perceived accuracy of weather forecasts, together with a comparison with the
corresponding figures from previous waves, is detailed below:
Respondents’ Opinions on the Accuracy of Weather Forecasts over the past Several Months
Level of Accuracy APR 2006
(%)
OCT 2006
(%)
APR 2007
(%)
OCT 2007
(%)
APR 2008
(%)
OCT 2008
(%)
APR 2009
(%)
OCT 2009
(%)
APR 2010
(%)
Accurate 83.6 71.1 71.0 68.3 69.1 71.0 77.1 77.5 76.2
Average 15.9 25.0 25.3 27.8 20.8 23.0 21.3 20.4 20.7
Inaccurate 0.6 3.6 2.1 2.1 6.6 2.5 1.2 1.5 3.0
No comment - 0.2 1.7 1.9 3.5 3.5 0.3 0.6 0.1
Sample Size* 980 973 964 971 960 1021 993 1004 1006
* Number of Active Respondents.
(Ref.: Question 8)
On evaluation of the accuracy of weather forecasts over the past several months, 88.9% of
respondents gave a rating of 70% or higher, whereas only 5.2% of respondents rated
50% or lower.
The average percentage of perceived accuracy of weather forecasts was 78.2%, which is
comparable to corresponding figures in previous waves, as shown in the table below:
Mean Percentage of Weather Forecasts over the Past Several Months Considered Accurate by
Respondents
APR 2006
(%)
OCT 2006
(%)
APR 2007
(%)
OCT 2007
(%)
APR 2008
(%)
OCT 2008
(%)
APR 2009
(%)
OCT 2009
(%)
APR 2010
(%)
Mean percentage 79.8 75.9 77.0 76.5 74.7 77.0 79.0 78.3 78.2
Remark: Sample size of each survey was different.
(Ref.: Question 9)
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
5 May 2010
When the accuracy of weather forecasts were further broken down into four aspects -
temperature forecast, fine/cloudy prediction, rainstorm forecast/warning and typhoon
prediction/warning over the past several months, most respondents (80.1% - 91.7%)
considered that the four aspects of weather forecasts were “accurate” or “somewhat
accurate”. However, the results indicated a slight decrease in the accuracy of weather
forecasts in those four aspects when compared with the figures from previous waves, as
given in the table below:
Respondents’ Opinions on the Accuracy Level of Different Aspects of Weather Forecasts
over the past Several Months
Level of Accuracy APR 2006
(%)
OCT 2006
(%)
APR 2007
(%)
OCT 2007
(%)
APR 2008
(%)
OCT 2008
(%)
APR 2009
(%)
OCT 2009
(%)
APR 2010
(%)
Temperature forecasts
Accurate/Somewhat
Accurate 95.0 95.1 92.9 92.2 85.9 88.1 94.2 95.1 91.7
Inaccurate/Somewhat
Inaccurate 4.2 3.7 4.2 4.8 7.6 8.2 5.5 4.0 7.9
No comment 0.8 1.2 2.8 3.0 6.5 3.7 0.2 0.9 0.4
Fine / cloudy predictions
Accurate/Somewhat
Accurate 92.9 90.8 86.8 82.4 81.4 82.4 88.9 88.0 85.4
Inaccurate/Somewhat
Inaccurate 5.9 8.0 8.5 13.5 13.9 13.7 10.7 10.4 13.1
No comment 1.2 1.2 4.7 4.1 4.7 3.9 0.4 1.6 1.5
Rain storm forecasts / warning
Accurate/Somewhat
Accurate 88.7 77.6 75.1 72.5 69.2 76.3 85.6 87.8 80.1
Inaccurate/Somewhat
Inaccurate 9.1 20.5 19.0 23.5 24.5 20.4 13.8 11.4 14.8
No comment 2.5 2.0 5.9 4.0 6.4 3.2 0.6 0.8 5.1
Typhoon prediction / warning
Accurate/Somewhat
Accurate 90.1 73.0 65.2 71.7 67.7 80.4 88.9 91.7 82.9
Inaccurate/Somewhat
Inaccurate 3.7 25.6 17.2 24.4 23.7 17.0 9.7 7.7 9.1
No comment 6.2 1.4 17.5 3.9 8.6 2.6 1.3 0.6 8.1
Sample Size* 980 973 964 971 960 1021 993 1004 1006
* Number of Active Respondents.
(Ref.: Question 10 – 13)
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
6 May 2010
For the accuracy of weather forecasts in comparison with the past 3 to 4 years, 65.2% of
respondents considered the current weather forecasts more accurate, 25.4% of
respondents claimed the accuracy remained the same. Among the respondents, 6.3%
considered the accuracy has declined; an increase of 3.1% from previous wave.
Respondents’ Opinions on the Accuracy of Weather Forecasts Nowadays
as Compared with those of 3 to 4 years ago
Level of Accuracy APR 2006
(%)
OCT 2006
(%)
APR 2007
(%)
OCT 2007
(%)
APR 2008
(%)
OCT 2008
(%)
APR 2009
(%)
OCT 2009
(%)
APR 2010
(%)
More accurate 70.1 50.4 60.5 59.7 54.5 63.2 65.4 67.1 65.2
About the same 26.5 40.1 30.9 30.1 31.4 25.8 29.5 26.9 25.4
Less accurate 1.4 7.5 3.9 5.8 6.8 3.2 3.8 3.2 6.3
Don’t know / No
comment 2.0 2.0 5.6 4.4 7.3 7.8 1.3 2.8 3.1
Sample Size* 980 973 964 971 960 1021 993 1004 1006
* Number of Active Respondents.
(Ref.: Question 14)
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
7 May 2010
Overall Satisfaction with the HKO’s Services
In terms of the overall satisfaction with the HKO’s services, most of the respondents (87.3%)
gave a rating of 7 or above, with mean score 7.8 which was comparable to corresponding
figures in previous waves:
Overall Satisfaction on the Services provided by the HKO over the Past Several Months (10-point
rating scale)
Level of Satisfaction OCT 2006
(%)
APR 2007
(%)
OCT 2007
(%)
APR 2008
(%)
OCT 2008
(%)
APR 2009
(%)
OCT 2009
(%)
APR 2010
(%)
0 – 3 1.5 0.8 0.5 1.1 0.4 0.1 0.8 0.8
4 – 6 16.3 14.4 17.2 15.9 9.7 11.1 10.8 12.0
7 – 10 82.2 84.7 76.7 81.7 87.9 88.8 88.4 87.3
Don’t know < 0.05 0.1 -- 1.3 2.0 -- -- --
Mean Score 7.4 7.6 7.5 7.5 7.8 7.8 7.8 7.8
Sample Size* 973 964 971 960 1021 993 1004 1006
* Number of Active Respondents.
(Ref.: Question 15)
In terms of the opinions towards the tropical cyclone warning services, as compared with
the past few years, more than 90% of total respondents considered the services better or
about the same as before. Only 3.4% of respondents believed the services are worse than
before.
Respondents’ Opinions on the Tropical Cyclone Warning Services Nowadays
as Compared with those of 3 to 4 years ago
Level of Accuracy APR 2010
(%)
Better 61.2
About the same 31.3
Worse 3.4
Don’t know / No comment 4.1
Sample Size* 1006
* Number of Active Respondents.
(Ref.: Question 16)
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
8 May 2010
2 Background
The Hong Kong Observatory (HKO) is a government department to deliver meteorological
services to the public. One of its important roles is to forecast the weather of the coming
days and to issue warning signals during hazardous weather situations.
Since 1989, the department has commissioned independent market research agencies to
conduct public opinion survey on the accuracy of weather forecasts and warnings issued by
HKO at half-yearly interval. In 2010, two waves of survey are planned to conduct in April
and October respectively.
Opinion Research Corporation (ORC) is pleased to submit this report. This document
presents the objectives, research design, methodology, analysis, and survey findings for
HKO’s reference.
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
9 May 2010
3 Objectives
The objectives of the survey are:
To gauge the public’s opinions on the accuracy of the following aspects:
o Temperature forecast
o Fine / Cloudy prediction
o Rain storm forecasts / warning
o Typhoon prediction / warning
To track HKO’s performance as perceived by the general public; and
To identify the popular channels used by the general public to receive weather
information
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
10 May 2010
4 Methodology
4.1 Survey Coverage
The survey covered people living in Hong Kong aged between 15 and 64.
4.2 Research Design
The pilot test was conducted on 8 April 2010 to test for the feasibility of the questionnaire
before the commencement of the main fieldwork. Consequently, 30 interviews were
successfully conducted in the pilot test, with interviewing time in the range of 5 to 7 minutes.
No problematic area was identified during the pilot test, and the original questionnaire was
implemented in the main survey as approved by the HKO.
Main Survey
In order to ensure the findings from the survey are representative, systematic random
sampling method was employed. A random sample of household telephone numbers were
selected from the telephone database maintained by ORC. Within the selected household,
a target respondent aged 15 to 64 was randomly picked by means of the “Kish Grid”
random selection method. Only one successful interview was conducted in each sampled
household.
In total, 1 008 individuals were successfully enumerated during the fieldwork period from 16
April to 30 April 2010, constituting an overall response rate of 75.9%. The enumeration
results are presented below:
Count
(a) Total number of telephone numbers selected 1 620
(b) Non contact cases 83
(c) Invalid cases 292
Non-operating numbers, fax numbers, non-residential numbers, etc. 133
Without eligible respondents aged 15-64 159
(d) Refusal 239
(e) Successful interviews 1 008
Overall response rate = (e) / [(b) + (d) + (e)] x 100% 75.9%
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
11 May 2010
4.3 Questionnaire Design
In order to meet the objectives stated in Section 3 above, the questionnaire (see Appendix I)
comprised the following three major parts:
Channels to access weather information
Perceptions on the services provided by the HKO
Demographic questions on the respondents
4.4 Statistical Analysis and Presentation of Survey Results
The statistical software, SPSS for Windows version 13.0 was used to perform all statistical
analyses. Office Word 2007 was employed to construct charts and graphs. Frequency
tables and cross tabulations were produced for each survey response. Note that for tables
presented in this report, figures may not add up to totals due to rounding. Statistical tests,
including Chi-square test and Fisher's exact test, were performed to test the relationship
between two categorical variables. Kruskal Wallis test and Mann-Whitney U test were
applied to check for significant differences between groups. To examine the association
among any two ordinal/interval measurements, Spearman's rho test was used.
Respondents who did not usually read, watch or listen to weather reports were excluded
from all statistical analyses. In addition, respondents who refused to answer a particular
question were excluded from all significant tests on that question.
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
12 May 2010
5 Detailed Findings
5.1 Demographic Profiles of Respondents
Of the 1 008 respondents interviewed during the fieldwork period, females accounted for a
higher proportion as compared to males (54.5% vs. 45.5%). While about two-fifth or more of
the respondents were of age 40 – 59 (45.2%) and 20 – 39 (39.5%), the youth (aged 15 – 19)
and the elderly (aged 60 – 64) respondents accounted for a lower proportion of 10.4% and
4.9% respectively.
Regarding the educational attainment, about three-fifths (58.6%) of the respondents had
secondary/matriculation education level, 32.0% of the respondents had attained tertiary or
above education level and 18.7% had primary or below education level.
45.8% of the respondents were non-working, with closed to one-fifth (19.5%) being
homemakers and 15.7 % being students; 4.1% were jobseekers and 6.5% has retired.
Among those who were economically active, 27.7% of the respondents were clerical staff
and 20.1% were associate professionals. The proportion of respondent who worked as
service or sales staff, managers or administrators, self-employed, technical staff, or
non-technical staff were 13.7%, 10.6%, 10.3%, 10.1% and 5.1%, respectively.
When further asked about their working industry, 29.1% of the respondents were working in
the industry of Community, Social and Personal service; 21.1% of them were working in the
industry of Wholesales, Retail and Import / Export trades, Restaurants and Hotels and
17.8% were in the Financing, Insurance, Real Estate and Business Service sector. About
equal proportions of the working respondents were in the Transport, Storage and
Communication and Construction sectors (10.1% and 9.2% respectively).
Regarding the monthly personal income, more than 15% of the respondents indicated that
they had an income level of $4,000 - $9,999 (18.1%), $1 - $3,999 (17.4%) and $10,000 -
$14,999 (17%). About equal proportions of the respondent claimed that they belonged to
the monthly household income group of $20,000 - $29,999 (18.0%) and $12,500 - $19,999
(17.0%). 13.6% of them had a monthly household income of $30,000 - $39,999 and 10.3%
had $1 - $12,499.
(Ref.: Appendix III, Tables 17 - 23)
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
13 May 2010
5.2 Degree of Concern about Weather Information
The majority of respondents (99.8%) indicated that they usually read, watch or listen to
weather reports, suggesting that the general public is well aware of the weather information
available to them.
The degree of concern about weather information has never dropped below 94% for the
past decade, and stayed around 99% for the past three waves of public opinion survey.
(Ref.: Appendix II, Chart 3)
5.3 Channels to Access Weather Information
5.3.1 Popularity of channels to access weather information
The majority of the respondents obtain weather information through traditional media
channels, such as television (96.8%), radio (47.1%) and newspaper (25.5%).
Not surprisingly, more and more members of the general public were searching for weather
information on the web. Specifically, 23.1% of the respondents regularly obtain weather
information via the HKO’s website, 1.9% seek information on other weather websites,
while 27.3% look for the relevant details on web portal such as MSN, Yahoo! and Google.
Approximately half (49.1%) of the respondents indicated that they frequently make use of 3
channels to access weather information, with more than one-third (38.3%) making use of 2
channels. Only 12.6% of the respondents merely obtain information from a single channel.
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
14 May 2010
Chart 1: Channels used by the respondents to access weather information
7%
8%
12%
70%
12%
9%
26%
24%
16%
10%
3%
1%
<2%
<2%
11%
<5%
<8%
7%
5%
Friends/Relatives
Mobile Phones
PCCW's 18501/18503/18508
HK Observatory's Dial-a Weather
hotlines 1878200
Other weather websites
Observatory's website
Other websites' weather
information section
Newspaper
Radio
Television
1st channel 2nd channel 3rd channel
Sample size = 1 006
Television remained as the most popular first channel (70.1%), followed by radio and web
portal (11.5% and 7.8% respectively). Radio was the most popular secondary channel
(25.5%), closely followed by television (23.9%).
PCs were still the most common (85.6%) devices used when accessing weather
information on the internet, a decrease of 6.3% from previous wave, possibly due to the
increasing utilization of WAP phones, PDAs and other handheld devices in recent years.
The corresponding figures for WAP phones and PDAs are 4% and 1%, respectively, with
6.1% used both the PCs and WAP phones, 1.1% used both the PCs and PDAs, and 2.3%
used all three devices.
(Ref.: Chart 1 & Appendix II, Chart 4)
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
15 May 2010
Cross Tabulation Analysis
Although respondents with low education attainment were less likely to seek
information from the internet, there weren’t trends across the respondent groups based
on the gender, occupation or age demographic variables.
The awareness of weather information is higher for the working classes, who were also
more likely to utilize alternative channels to obtain weather information. For instance
technical people on average used 2.47 channels, against 2.12 channels for those who
have retired.
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
16 May 2010
5.4 Opinions towards the Accuracy of Weather Forecasts over the
Past Several Months
5.4.1 Overall accuracy level of weather forecasts
The general public was asked for their opinion whether the weather forecasts issued by
HKO over the period of 3 - 6 months immediately before this survey were accurate.
Although there was strong agreement among the respondents (76.2%) that the weather
forecasts were accurate, yet some 3% of respondents expressed an opposite opinion, a
slight increase from previous waves (1.2% in April 2009, 1.5% in October 2009). Just over
twenty percentages of respondents perceived the accuracy as average.
(Ref.: Table 1 & Appendix III, Table 11)
Table 1: Respondents’ Opinions on the Accuracy of Weather Forecasts over the past Several Months
Level of Accuracy APR 2006
(%)
OCT 2006
(%)
APR 2007
(%)
OCT 2007
(%)
APR 2008
(%)
OCT 2008
(%)
APR 2009
(%)
OCT 2009
(%)
APR 2010
(%)
Accurate 83.6 71.1 71.0 68.3 69.1 71.0 77.1 77.5 76.2
Average 15.9 25.0 25.3 27.8 20.8 23.0 21.3 20.4 20.7
Inaccurate 0.6 3.6 2.1 2.1 6.6 2.5 1.2 1.5 3.0
No comment - 0.2 1.7 1.9 3.5 3.5 0.3 0.6 0.1
Sample Size* 980 973 964 971 960 1021 993 1004 1006
* Number of Active Respondents.
Cross Tabulation Analysis
Respondents working in the Electricity, Gas and Water or Construction industries were
more likely to agree with the predictions of HKO.
Based on the Spearman’s rho correlation test, a positive correlation was observed between
age groups and the accuracy levels (p-value =0.000, r =0.217). However, a negative
correlation was observed between education attainments and the accuracy levels (p-value
=0.009, r = -0.083)
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
17 May 2010
5.4.2 Percentage of accurate weather forecasts
The general public was also asked to comment on the proportion of accurate weather
forecasts, expressed in percentage, issued by HKO over the same time period.
Close to ninety percent (88.9%) of the respondents reckoned that 70% or more of the
weather forecast were accurate. Only a low proportion of the respondents (5.2%) rated
50% or less of the forecast were correct.
The modal percentage score is 80%, with three hundreds and forty-three respondents
(34.3%) gave this rating; another 21.0% of respondents gave a score of 90%, indicating a
high level of accuracy as perceived by the public.
The mean percentage is effectively unchanged from previous wave (78.2% vs 78.3%).
(Ref.: Table 2, Appendix II, Chart 5 & Appendix III, Table 12)
Table 2: Mean Percentage of Weather Forecasts over the Past Several Months Considered Accurate
APR 2006
(%)
OCT 2006
(%)
APR 2007
(%)
OCT 2007
(%)
APR 2008
(%)
OCT 2008
(%)
APR 2009
(%)
OCT 2009
(%)
APR 2010
(%)
Mean percentage 79.8 75.9 77.0 76.5 74.7 77.0 79.0 78.3 78.2
Remark: Sample size of each survey was different.
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
18 May 2010
5.4.3 Accuracy level of different aspects of weather forecasts
The general public was further asked about the accuracy of weather forecast services on
four aspects, viz. temperature forecast, fine/cloudy prediction, rainstorm forecast/warning
and typhoon prediction/warning.
More than ninety percent (91.7%) of respondents considered the temperature forecasts
were “accurate” or “somewhat accurate”. Eighty-five percent (85.4%) agreed that the
fine/cloudy predictions were “accurate” or “somewhat accurate”. The figures for rainstorm
forecast/warning and typhoon prediction/warning were 80.1% and 82.9%, respectively.
(Ref.: Chart 2 & Appendix III, Table 13)
Chart 2: Perception of accuracy level of four aspects of weather forecasts
46%
39%
39%
38%
37%
42%
46%
54%
14%
12%
7%
8% 8%
5%
2%
1%
Typhone prediction /
warning
Rain storm forecasts /
warning
Fine / Cloudy weather
forecasts
Temperature
Accurate Somewhat accurate Somewhat inaccurate Inaccurate Don't know / No comment
Sample size: All Active Respondents (1 006)
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
19 May 2010
The percentage of respondents who indicated that the forecasts in these four aspects were
“accurate” or “somewhat accurate” has decreased slightly when compared to previous
waves in 2009.
(Ref.: Table 3)
Table 3: Respondents’ Opinions on the Accuracy Level of Different Aspects of Weather Forecasts
over the past Several Months
Level of Accuracy APR 2006
(%)
OCT 2006
(%)
APR 2007
(%)
OCT 2007
(%)
APR 2008
(%)
OCT 2008
(%)
APR 2009
(%)
OCT 2009
(%)
APR 2010
(%)
Temperature forecasts
Accurate/Somewhat
Accurate 95.0 95.1 92.9 92.2 85.9 88.1 94.2 95.1 91.7
Inaccurate/Somewhat
Inaccurate 4.2 3.7 4.2 4.8 7.6 8.2 5.5 4.0 7.9
No comment 0.8 1.2 2.8 3.0 6.5 3.7 0.2 0.9 0.4
Fine / cloudy predictions
Accurate/Somewhat
Accurate 92.9 90.8 86.8 82.4 81.4 82.4 88.9 88.0 85.4
Inaccurate/Somewhat
Inaccurate 5.9 8.0 8.5 13.5 13.9 13.7 10.7 10.4 13.1
No comment 1.2 1.2 4.7 4.1 4.7 3.9 0.4 1.6 1.5
Rain storm forecasts / warning
Accurate/Somewhat
Accurate 88.7 77.6 75.1 72.5 69.2 76.3 85.6 87.8 80.1
Inaccurate/Somewhat
Inaccurate 9.1 20.5 19.0 23.5 24.5 20.4 13.8 11.4 14.8
No comment 2.5 2.0 5.9 4.0 6.4 3.2 0.6 0.8 5.1
Typhoon prediction / warning
Accurate/Somewhat
Accurate 90.1 73.0 65.2 71.7 67.7 80.4 88.9 91.7 82.9
Inaccurate/Somewhat
Inaccurate 3.7 25.6 17.2 24.4 23.7 17.0 9.7 7.7 9.1
No comment 6.2 1.4 17.5 3.9 8.6 2.6 1.3 0.6 8.1
Sample Size* 980 973 964 971 960 1021 993 1004 1006
* Number of Active Respondents.
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
20 May 2010
5.5 Overall Satisfaction with the Hong Kong Observatory’s Services
over the Past Several Months
This measure examines the percentage of the general public who were satisfied with the
services provided by the HKO in the past 3 – 6 months immediately before this survey.
On a 10-point scale, with 0 represents "poor service" and 10 represents "excellent
service" the overall satisfaction level with the HKO’s services remained high over the
years. The mean score was 7.8, representing no deterioration since 2008.
Among the respondents, 87.3% gave a rating of 7 or above. The mode of this measure
was 8, with about two-fifth (38.2%) of respondents who gave this rating. Eighty-two
respondents (8.2%) gave HKO’s services a full mark.
(Ref.: Table 4 & Appendix III, Table 15)
Table 4: Overall Satisfaction on the Services provided by the HKO over the Past Several Months
(10-point rating scale)
Level of Satisfaction OCT 2006
(%)
APR 2007
(%)
OCT 2007
(%)
APR 2008
(%)
OCT 2008
(%)
APR 2009
(%)
OCT 2009
(%)
APR 2010
(%)
0 – 3 1.5 0.8 0.5 1.1 0.4 0.1 0.8 0.8
4 – 6 16.3 14.4 17.2 15.9 9.7 11.1 10.8 12.0
7 – 10 82.2 84.7 76.7 81.7 87.9 88.8 88.4 87.3
Don’t know < 0.05 0.1 -- 1.3 2.0 -- -- --
Mean Score 7.4 7.6 7.5 7.5 7.8 7.8 7.8 7.8
Sample Size* 973 964 971 960 1021 993 1004 1006
* Number of Active Respondents.
(Ref.: Appendix II, Chart 11)
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
21 May 2010
5.6 Accuracy Level when Compared to 3 or 4 Years Ago
5.6.1 Comparison: Accuracy Level of Current Weather Forecasts
For the accuracy of weather forecasts in comparison with the past 3 to 4 years, 65.2% of
respondents reckoned that the current weather forecasts more accurate, 25.4% of
respondents claimed the accuracy remained the same. The rest (6.3%) considered the
accuracy has declined, slight increase of 3.1% from previous wave.
(Ref.: Table 5, Appendix II, Chart 10 & Appendix III, Table 14)
Table 5: Respondents’ Opinions on the Accuracy of Weather Forecasts Nowadays
as Compared with those of 3 to 4 years ago
Level of Accuracy APR 2006
(%)
OCT 2006
(%)
APR 2007
(%)
OCT 2007
(%)
APR 2008
(%)
OCT 2008
(%)
APR 2009
(%)
OCT 2009
(%)
APR 2010
(%)
More accurate 70.1 50.4 60.5 59.7 54.5 63.2 65.4 67.1 65.2
About the same 26.5 40.1 30.9 30.1 31.4 25.8 29.5 26.9 25.4
Less accurate 1.4 7.5 3.9 5.8 6.8 3.2 3.8 3.2 6.3
Don’t know / No
comment 2.0 2.0 5.6 4.4 7.3 7.8 1.3 2.8 3.1
Sample Size* 980 973 964 971 960 1021 993 1004 1006
* Number of Active Respondents.
Reviewing the data over the years, the accuracy levels of this measure seems to fluctuate
from one season to another, which reflects the perceived performance of the HKO over a
longer period carries strong seasonal variations.
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
22 May 2010
5.6.2 Comparison: Accuracy Level of Current Tropical Cyclone Warning Services
In respect of the opinions towards the tropical cyclone warning services, as compared with
the past few years, more than 90% of total respondents considered the services better or
about the same as before. Only 3.4% of respondents claimed the services are worse than
before.
Table 6: Respondents’ Opinions on the Tropical Cyclone Warning Services Nowadays
as Compared with those of 3 to 4 years ago
Level of Accuracy APR 2010
(%)
Better 61.2
About the same 31.3
Worse 3.4
Don’t know / No comment 4.1
Sample Size* 1006
* Number of Active Respondents.
(Ref.: Table 5 & Appendix III, Table 16)
This is a new question added in this wave, and therefore comparisons to previous years
were not available.
Cross Tabulation Analysis
Based on the results of the Spearman’s rho test, there was no significant relationship
between monthly income and the perception of accuracy level of current tropical cyclone
warning services.
Regarding the Kruskal Wallis tests, the results showed that no significant variation of
perceived accuracy among working respondents in different occupation and industry. For
the non-working respondents, homemakers and retired persons were likely to consider the
tropical cyclone warning services to be accurate.
Significant relationships were also observed for age groups and education attainments
against the level of accuracy in this measure. Generally speaking; the higher the age group,
the higher is the perceived accuracy (p-value =0.000, r =0.241); and the higher the
education attainments, the lower is the perceived accuracy (p-value =0.000, r = -0.184)
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
23 May 2010
Appendix I: Questionnaire
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
24 May 2010
Public Opinion Survey on the Accuracy of Weather Forecasts 2010
Tel. Code:
Name of Respondent: Contact Tel. Number:
Interviewer ID: Interview Date:
Start Time of Interview: End Time of Interview:
Introduction:
Good morning/afternoon/evening, my name is _____________ and I am calling from ORC International, an
independent research firm. We have been commissioned by Hong Kong Observatory (HKO) to conduct an
opinion survey on the accuracy of weather forecasts in Hong Kong and would like to conduct a short interview
with you. The information you provide will be treated with strict confidence and will be used for aggregate
analysis only. Thank you for your cooperation.
Screening
We wish to invite one of your household members to conduct the interview by a random selection method.
May I know how many household members are aged 15 to 64 in your household? Who is the eldest? Then
who is the next eldest…? (Please exclude the live-in domestic helper)
(Selection of respondent: List all household members aged 15 to 64, from the eldest to the youngest.
Circle the last digit of the Tel. Code. Move along the column right under this digit, and circle the
corresponding figure on the row where the youngest household member belongs to. Then interview the
household member whose code number is same as the figure.)
Household members aged 15 to 64 Last digit of the Tel. Code
Code (from the eldest to the youngest) 1 2 3 4 5 6 7 8 9 0
1. 1 1 1 1 1 1 1 1 1 1
2. 2 1 2 1 2 1 2 1 2 1
3. 2 3 1 2 3 1 2 3 1 2
4. 3 4 1 2 3 4 1 2 3 4
5. 5 1 2 3 4 5 1 2 3 4
6. 5 6 1 2 3 4 5 6 1 2
7. 3 4 5 6 7 1 2 3 4 5
8. 6 7 8 1 2 3 4 5 6 7
9. 8 9 1 2 3 4 5 6 7 8
10. 9 10 1 2 3 4 5 6 7 8
According to the information you provided, we have randomly selected (the selected household member) for
the interview. Can I talk to him/her? (If the selected respondent is not available, arrange the interview for
another date and time.)
(If the selected respondent is not the one you first talked to, repeat the introduction; otherwise start with Q1)
RESTRICTED when entered with data
Accessible to authorized persons only
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
25 May 2010
Q1. Do you usually read, watch or listen to weather reports?
1. Yes
2. No -> Jump to Q17
Q2. From where do you usually obtain weather information of Hong Kong? Do you obtain from radio,
Television, newspaper, weather hotline, internet, pagers / mobile phones, or other sources? [SA]
[For “weather hotline”, probe: Is it Hong Kong Observatory’s Dial-a-Weather hotlines 1878-200, or
PCCW’s 18-501 and 18-503, 18-508?]
[For “internet”, probe: Is it Hong Kong Observatory’s website or other weather websites or other
websites’ weather information section?]
1. Radio -> Jump to Q4
2. Television -> Jump to Q4
3. Newspaper -> Jump to Q4
4. Hong Kong Observatory’s Dial-a-Weather hotlines 1878 200 -> Jump to Q4
5. PCCW’s 18 501 / 18 503 / 18 508 -> Jump to Q4
6. Observatory’s website
7. Other weather websites
8. Other websites’ weather information section (e.g. yahoo)
9. Mobile Phones -> Jump to Q4
10. Pagers -> Jump to Q4
11. Friends or relatives -> Jump to Q4
12. Other sources, please specify: -> Jump to Q4
Q3. As you mentioned, you obtain weather information from Internet. Did you use PC, WAP Mobile phone
or PDA to access internet for obtaining weather information? [MA]
1. Personal Computer (PC)
2. WAP phone
3. Personal Digital Assistant (PDA)
4. Others, please specify: _______________________
Q4. Any others (any other source for obtaining weather information of Hong Kong)? [SA]
[For “weather hotline”, probe: Is it Hong Kong Observatory’s Dial-a-Weather hotlines 1878-200, or
PCCW’s 18-501 and 18-503, 18-508?]
[For “internet”, probe: Is it Hong Kong Observatory’s website or other weather websites or other
websites’ weather information section?]
1. Radio -> Jump to Q6
2. Television -> Jump to Q6
3. Newspaper -> Jump to Q6
4. Hong Kong Observatory’s Dial-a-Weather hotlines 1878 200 -> Jump to Q6
5. PCCW’s 18 501 / 18 503 / 18 508 -> Jump to Q6
6. Observatory’s website
7. Other weather websites
8. Other websites’ weather information section (e.g. yahoo)
9. Mobile Phones -> Jump to Q6
10. Pagers -> Jump to Q6
11. Friends or relatives -> Jump to Q6
12. Other sources, please specify: -> Jump to Q6
13. No more -> Jump to Q8
Main Questionnaire
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
26 May 2010
Q5. As you mentioned, you obtain weather information from Internet. Did you use PC, WAP Mobile phone
or PDA to access internet for obtaining weather information? [MA]
1. Personal Computer (PC)
2. WAP phone
3. Personal Digital Assistant (PDA)
4. Others, please specify:____________________________
Q6. Any more (any other source for obtaining weather information of Hong Kong )? [SA]
[For “weather hotline”, probe: Is it Hong Kong Observatory’s Dial-a-Weather hotlines 1878-200, or
PCCW’s 18-501 and 18-503, 18-508?]
[For “internet”, probe: Is it Hong Kong Observatory’s website or other weather websites or other
websites’ weather information section?]
1. Radio -> Jump to Q8
2. Television -> Jump to Q8
3. Newspaper -> Jump to Q8
4. Hong Kong Observatory’s Dial-a-Weather hotlines 1878 200 -> Jump to Q8
5. PCCW’s 18 501 / 18 503 / 18 508 -> Jump to Q8
6. Observatory’s website
7. Other weather websites
8. Other websites’ weather information section (e.g. yahoo)
9. Mobile Phones -> Jump to Q8
10. Pagers -> Jump to Q8
11. Friends or relatives -> Jump to Q8
12. Other sources, please specify: -> Jump to Q8
13. No more -> Jump to Q8
Q7. As you mentioned, you obtain weather information from Internet. Did you use PC, WAP Mobile phone
or PDA to access internet for obtaining weather information? [MA]
1. Personal Computer (PC)
2. WAP phone
3. Personal Digital Assistant (PDA)
4. Others, please specify: ____________________________
Q8. Do you consider the weather forecasts of the Hong Kong Observatory over the past several months
very accurate, somewhat accurate, average, somewhat inaccurate or very inaccurate?
1. Very accurate
2. Somewhat accurate
3. Average
4. Somewhat inaccurate
5. Very inaccurate
6. Don’t know / No comment (Don’t mention)
Q9. What percentage of weather forecasts of the Hong Kong Observatory over the past several months do
you consider accurate?
1. ____________ per cent
2. Don’t know / No comment (Don’t mention)
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
27 May 2010
Do you consider the following aspects of weather forecasts of the Hong Kong Observatory over the past
several months accurate, somewhat accurate, somewhat inaccurate or inaccurate?
Accurate Somewhat
accurate
Somewhat
inaccurate Inaccurate
Don’t know /
No comment
(Don’t mention)
Q10. Temperature 1 2 3 4 5
Q11. Fine / Cloudy 1 2 3 4 5
Q12. Rain storm forecasts /
warning 1 2 3 4 5
Q13. Typhoon prediction /
warning 1 2 3 4 5
Q14. How do you compare weather forecasts nowadays with those 3 to 4 years ago? Is it more accurate,
less accurate or about the same?
1. More accurate
2. About the same
3. Less accurate
4. Don’t know / No comment (Don’t mention)
Q15. If you rate on a scale of 0 to 10, with “10” being “excellent service”, “5” the passing mark and “0” “poor
service”, how many marks will you give for the satisfaction level of the services provided by the Hong
Kong Observatory? ______________ Mark
Q16. How do you compare the tropical cyclone warning services provided by the Hong Kong Observatory
nowadays with those from the past 3 to 4 years ago? Is it better, worse or about the same?
1. Better
2. About the same
3. Worse
4. Don’t know / No comment (Don’t mention)
Personal Information
Finally, we would like to ask you some personal information. This information is collected for statistical
analysis only and will be kept confidential.
Q17. Which age group do you belong to?
1. 15-17
2. 18-19
3. 20-29
4. 30-39
5. 40-49
6. 50-59
7. 60-64
8. Refuse to answer
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
28 May 2010
Q18. What is your educational attainment?
1. No formal schooling/kindergarten
2. Primary
3. Junior secondary (Form 1 to Form 3)
4. Senior secondary (Form 4 to Form 5)/Springboard Project
5. Matriculation (Form 6 to Form 7)/Technical College
6. Tertiary (non-degree or associate degree)
7. Bachelor Degree
8. Master or Doctor Degree
9. Refuse to answer
Q19. What is your occupation? (If answer – no occupation, ask whether it belongs to 1, 2, 3, or 4)
1. Student -> Jump to Q21
2. Homemaker -> Jump to Q21
3. Job seeker / unemployed -> Jump to Q21
4. Retired -> Jump to Q21
5. Professionals or associate professionals
6. Managers or administrators
7. Clerical staff
8. Technical staff
9. Non-technical staff
10. Service or sales staff
11. Self-employed
12 Others, please specify: ____________________
13. Refuse to answer
Q20. Which of the industry are you engaged in?
1. Agriculture and Fishing
2. Mining and Quarrying
3. Manufacturing
4. Electricity, Gas and Water
5. Construction
6. Wholesale, Retail and Import/Export Trades, Restaurants and Hotels
7. Transport, Storage and Communication
8. Financing, Insurance, Real Estate and Business Services
9. Community, Social and Personal Services
10. Other, please specify:_____________________
11. Refuse to answer
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
29 May 2010
Q21. Which personal monthly income group do you belong to? (including salary, housekeeping money,
government subsidy, old age allowance, CSSA, etc)
1. No income
2. $1-3,999
3. $4,000-9,999
4. $10,000-14,999
5. $15,000-19,999
6. $20,000-29,999
7. $30,000-39,999
8. $40,000 or above
9. Refuse to answer
Q22. Which household monthly income group do you belong to? (including salary, housekeeping
money, government subsidy, old age allowance, CSSA, etc)
1. No income
2. $1-12,499
3. $12,500-19,999
4. $20,000-29,999
5. $30,000-39,999
6. $40,000-49,999
7. $50,000-59,999
8. $60,000-69,999
9. $70,000 or above
10. Refuse to answer
Q23. Gender
1. Male
2. Female
3. Refuse to answer
~ Thank you for your co-operation! ~
[Read out] Another staff of our company may contact you later to re-confirm the interview that I have done or
to clarify some other questions. He/she will ask a few questions only and will not disturb you for a long time.
Interviewer declaration
I hereby authenticate the data accuracy and integrity, and the interview was conducted by following the
guidelines maintained by the international standard of market research.
Signature: Date:
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
30 May 2010
Appendix II: Charts
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
31 May 2010
Chart 3: Overall Awareness of Weather Forecasts (April 99 – April 10)
Remark: Sample size of each survey was different.
Note: * denotes figure less than 0.5%.
100%100%99%96%94%97%96%97%98%97%97%95%96%97%97%97%96%96%96%98%97%98%98%
4%6%3%4%3%2%3%3%5%4%3%3%3%4%4%4%2%3%2%2% * *1%
Apr
10
Oct
09
Apr
09
Oct
08
Apr
08
Oct
07
Apr
07
Oct
06
Apr
06
Oct
05
Apr
05
Oct
04
Apr
04
Oct
03
Apr
03
Oct
02
Apr
02
Oct
01
Apr
01
Oct
00
Apr
00
Oct
99
Apr
99
Aware Not aware
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
32 May 2010
Chart 4: Popularity of Channels Used to Access Weather Information (April 99 – April 10)
Remark: Sample size of each survey was different.
47
3841
44
48
39
47464546
42
4950
43
57
4648
53
49
5351
55
9793
9594939294
9696949494
96959595959595949696
94
26
212118
13
2118
21
25
211918
21
172020
22222020
26
1517
74
65456675
8567
978787677
53
546
4569
57
912
71110
16
11
1613
1612
17
2326
23
5
9111213
11888765444322
53 212122212
5433323111
27.3
12
22
56
1714
1816
5777
35544
1 21210000000000000001101 0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
Apr
10
Oct
09
Apr
09
Oct
08
Apr
08
Oct
07
Apr
07
Oct
06
Apr
06
Oct
05
Apr
05
Oct
04
Apr
04
Oct
03
Apr
03
Oct
02
Apr
02
Oct
01
Apr
01
Oct
00
Apr
00
Oct
99
Apr
99
Pe
rce
nta
ge
(%
)
Radio TelevisionNewspaper HKO's Dial-a-Weather hotlinesPCCW's hotline HKO's WebsiteOther Weather websites Other Websites' weather information sectionMobile phones
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
33 May 2010
Chart 5: Mean Percentage of Accurate Weather Forecasts over the Past Several Months (April 99 – April 10)
Remark: Sample size of each survey was different.
74.7%
76.5%
77.0%
75.9%
79.8%
77.8%
79.7%
79.3%
77.5%
75.1%
75.7%
76.5%
77.7%
76.7%
77.0%
77.3%
77.4%
80.2%79.8%
77.7%
79.0%
78.3%
78.2%
Apr
10
Oct
09
Apr
09
Oct
08
Apr
08
Oct
07
Apr
07
Oct
06
Apr
06
Oct
05
Apr
05
Oct
04
Apr
04
Oct
03
Apr
03
Oct
02
Apr
02
Oct
01
Apr
01
Oct
00
Apr
00
Oct
99
Apr
99
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
34 May 2010
Chart 6: Perceived Accuracy of Forecasts on Temperature over the Past Several Months (April 99 – April 10)
Remark: Sample size of each survey was different.
Note: * Less than 0.5%.
92%95%94%
88%86%92%93%95%95%
92%95%93%92%94%92%93%94%93%
84%91%
84%
95%93%
4%6%
8%7%
5%4%4%4%
6%4%
3%4%3%7%5%4%5%
11%
5%
7%
4%5%
4%7%
3%3%1%1%2%1%4%4%3%1%2%2%2%
5%4%9%
1%2%8%
* *1%
Apr
10
Oct
09
Apr
09
Oct
08
Apr
08
Oct
07
Apr
07
Oct
06
Apr
06
Oct
05
Apr
05
Oct
04
Apr
04
Oct
03
Apr
03
Oct
02
Apr
02
Oct
01
Apr
01
Oct
00
Apr
00
Oct
99
Apr
99
Accurate Inaccurate Don't know
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
35 May 2010
Chart 7: Perceived Accuracy of Fine / Cloudy Weather Forecasts over the Past Several Months (April 99 – April 10)
Remark: Sample size of each survey was different.
Note: * Less than 0.5%.
85%88%89%82%81%82%
87%91%93%
90%93%
88%86%90%88%87%87%88%81%
84%79%
82%82%
13%10%11%
14%14%14%9%
8%6%8%
6%
7%6%8%11%11%
8%10%
14%10%
11%
16%15%
2%4%5%4%4%1%1%2%1%
5%5%2%1%2%
5%2%
5%6%10%
2%3% * 2%
Apr
10
Oct
09
Apr
09
Oct
08
Apr
08
Oct
07
Apr
07
Oct
06
Apr
06
Oct
05
Apr
05
Oct
04
Apr
04
Oct
03
Apr
03
Oct
02
Apr
02
Oct
01
Apr
01
Oct
00
Apr
00
Oct
99
Apr
99
Accurate Inaccurate Don't know
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
36 May 2010
Chart 8: Perceived Accuracy of Rainstorm Forecasts / Warning over the Past Several Months (April 99 – April 10)
Remark: Sample size of each survey was different.
80%
88%86%
76%69%
73%75%78%
88%86%89%
81%80%84%86%
71%
81%77%
80%81%81%77%75%
15%
11%14%
21%
25%24%19%
20%
9%12%7%
13%14%13%
13%
26%11%
21%14%14%11%
21%19%
1%3%6%4%6%
2%3%2%4%6%6%3%1%3%
9%2%
6%5%9%
2%6% 5%
1%
Apr
10
Oct
09
Apr
09
Oct
08
Apr
08
Oct
07
Apr
07
Oct
06
Apr
06
Oct
05
Apr
05
Oct
04
Apr
04
Oct
03
Apr
03
Oct
02
Apr
02
Oct
01
Apr
01
Oct
00
Apr
00
Oct
99
Apr
99
Accurate Inaccurate Don't know
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
37 May 2010
Chart 9: Perceived Accuracy of Typhoon Prediction / Warning over the Past Several Months (April 99 – April 10)
Remark: Sample size of each survey was different.
83%
92%89%
80%
68%72%
65%
73%
90%93%92%90%
86%
94%90%
86%
77%83%81%
86%80%
83%77%
9%
8%10%
17%
24%
24%
17%
26%
4%5%
3%6%
4%
5%8%
13%
7%
15%
7%
10%
4%
16%
7%
1%3%8%
4%
18%
1%6%
2%5%4%
10%
1%2%1%
16%
2%
12%
4%
16%
1%
16%
8%1%
Apr
10
Oct
09
Apr
09
Oct
08
Apr
08
Oct
07
Apr
07
Oct
06
Apr
06
Oct
05
Apr
05
Oct
04
Apr
04
Oct
03
Apr
03
Oct
02
Apr
02
Oct
01
Apr
01
Oct
00
Apr
00
Oct
99
Apr
99
Accurate Inaccurate Don't know
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
38 May 2010
Chart 10: Perceived Accuracy of Current Weather Forecasts as Compared with Those of 3 to 4 Years ago (April 99 – April 10)
Remark: Sample size of each survey was different.
65%67%65%63%
55%60%61%
50%
70%63%
70%67%
71%69%
59%55%
66%64%68%
71%76%
70%76%
25%27%30%
26%
31%
30%30%
40%
26%34%
27%27%
24%27%
37%
35%
29%29%
25%24%
19%26%
19%
6%4%
3%7%6%4%7%
1%2%2%
1%2%2%3%
6%2%4%4%1%1%
3%2%3%
8%7%4%5%3%3%1%1%5%3%3%1%4%3%3%3%4%4%1%3%
3%
3%1%
Apr
10
Oct
09
Apr
09
Oct
08
Apr
08
Oct
07
Apr
07
Oct
06
Apr
06
Oct
05
Apr
05
Oct
04
Apr
04
Oct
03
Apr
03
Oct
02
Apr
02
Oct
01
Apr
01
Oct
00
Apr
00
Oct
99
Apr
99
More Accurate More or Less the Same Less Accurate No comment
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
39 May 2010
Chart 11: Satisfaction Level with Overall Services Provided by the HKO over the Past Several Months (April 99 – April 10)
Remark: Sample size of each survey was different.
7.67.67.87.87.87.8
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Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
40 May 2010
Appendix III: Frequency Tables of Survey Findings
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
41 May 2010
Table 7: Respondents’ habit on reading, watching or listening to weather reports (Q1)
Frequency Percent Valid Percent
Cumulative
Percent
Valid Yes 1006 99.8 99.8 99.8
No 2 0.2 0.2 100.0
Total 1008 100.0 100.0
Base: All respondents
Table 8: Channels used to access weather information (Q2, Q4 & Q6)
1st Channel 2nd Channel 3rd Channel Total
Count % Count % Count % Count %
Radio 116 11.5% 257 25.5% 101 10.0% 474 47.1%
Television 705 70.1% 240 23.9% 29 2.9% 974 96.8%
Newspaper 6 0.6% 86 8.5% 165 16.4% 257 25.5%
Hong Kong
Observatory’s
Dial-a-Weather
hotlines 1878 200
17 1.7% 26 2.6% 28 2.8% 71 7.1%
PCCW’s 18 501 / 18
503 / 18 508 5 0.5% 18 1.8% 26 2.6% 49 4.9%
Observatory’s
website 74 7.4% 111 11.0% 47 4.7% 232 23.1%
Other weather
websites 2 0.2% 11 1.1% 6 0.6% 19 1.9%
Other websites’
weather information
section (e.g. yahoo)
78 7.8% 123 12.2% 74 7.4% 275 27.3%
Mobile Phones 2 0.2% 7 0.7% 9 0.9% 18 1.8%
Friends or relatives 1 0.1% -- -- 9 0.9% 10 1.0%
No more -- -- 127 12.6% 512 50.9% -- --
Total 1006 100.0% 1006 100.0% 1006 100.0% 1006 100.0%
Base: All Active Respondents
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
42 May 2010
Table 9: Channels used to access weather information (Q3, Q5 & Q7)
Frequency Percent
PC 450 85.6
WAP phone 21 4.0
PDA 5 1.0
Both PC and WAP phone 32 6.1
Both PC and PDA 6 1.1
Both PC, WAP phone and PDA 12 2.3
Total 526 100.0%
Base: All respondents who access weather information through the Internet
Table 10: Number of channels used to access weather information (Q3, Q5 & Q7)
Frequency Percent Valid Percent
Cumulative
Percent
Valid 1 127 12.6 12.6 12.6
2 385 38.2 38.3 50.9
3 494 49.0 49.1 100.0
Total 1006 100.0 100.0
Base: All Active Respondents
Table 11: Overall accuracy level on weather forecasts over the past several months (Q8)
Frequency Percent Valid Percent
Cumulative
Percent
Valid Very accurate 166 16.5 16.5 16.5
Somewhat accurate 601 59.7 59.7 76.2
Average 208 20.7 20.7 96.9
Somewhat inaccurate 25 2.5 2.5 99.4
Very inaccurate 5 0.5 0.5 99.9
Don't know / No comment 1 0.1 0.1 100.0
Total 1006 100.0 100.0
Base: All Active Respondents
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
43 May 2010
Table 12: Percentage of accurate weather forecasts over the past several months (Q9)
Frequency Percent Valid Percent
Cumulative
Percent
Valid
10 2 0.2 0.2 0.2
20 1 0.1 0.1 0.3
30 6 0.6 0.6 0.9
35 1 0.1 0.1 1.0
40 10 1.0 1.0 2.0
45 1 0.1 0.1 2.1
50 31 3.1 3.1 5.2
55 2 0.2 0.2 5.4
60 53 5.3 5.3 10.7
65 4 0.4 0.4 11.1
70 177 17.7 17.7 28.8
75 47 4.7 4.7 33.5
76 1 0.1 0.1 33.6
78 1 0.1 0.1 33.7
80 343 34.3 34.3 68.0
85 51 5.1 5.1 73.1
89 2 0.2 0.2 73.3
90 210 21.0 21.0 94.3
93 1 0.1 0.1 94.4
95 30 3.0 3.0 97.4
96 2 0.2 0.2 97.6
97 3 0.3 0.3 97.9
98 8 0.8 0.8 98.7
99 3 0.3 0.3 99.0
100 10 1.0 1.0 100.0
Total 1006 100.0 100.0
Mean 78.2
Median 80.0
Standard deviation 12.4
Base: All Active Respondents
Table 13: Perception of accurate weather forecasts over the past several months (Q10-Q13)
Temperature Fine / Cloudy Rain storm Typhoon
Count % Count % Count % Count %
Accurate 380 37.8% 392 39.6% 389 38.7% 463 46.0%
Somewhat accurate 543 54.0% 467 48.4% 417 41.5% 371 36.9%
Somewhat inaccurate 73 7.3% 119 9.9% 141 14.0% 83 8.3%
Inaccurate 6 0.6% 13 0.5% 8 0.8% 8 0.8%
Don't know / No
comment 4 0.4% 15 1.6% 51 5.1% 81 8.1.%
Total 1006 100.0% 1006 100.0% 1006 100.0% 1006 100.0%
Base: All Active Respondents
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
44 May 2010
Table 14: Comparison between current weather forecasts with those 3 to 4 years ago (Q14)
Frequency Percent Valid Percent
Cumulative
Percent
Valid More accurate 656 65.2 65.2 65.2
About the same 256 25.4 25.4 90.7
Less accurate 63 6.3 6.3 96.9
Don't know / No comment 31 3.1 3.1 100.0
Total 1006 100.0 100.0
Base: All Active Respondents
Table 15: Satisfaction level on weather services provided by the Hong Kong Observatory over the past
several months (Q15)
Frequency Percent Valid Percent
Cumulative
Percent
Valid 0.00 1 0.1 0.1 0.1
1.00 1 0.1 0.1 0.2
2.00 3 0.3 0.3 0.5
3.00 3 0.3 0.3 0.8
4.00 3 0.3 0.3 1.1
5.00 61 6.1 6.1 7.2
6.00 56 5.6 5.6 12.7
7.00 230 22.9 22.9 35.6
8.00 384 38.2 38.2 73.8
9.00 182 18.2 18.2 91.8
10.00 82 8.1 8.1 100.0
Total 1006 100.0 100.0
Mean 7.76
Median 8.00
Standard deviation 1.34
Base: All Active Respondents
Table 16: Comparison between current Tropical Cyclone Warning Services
with those 3 to 4 years ago (Q16)
Frequency Percent Valid Percent
Cumulative
Percent
Valid More accurate 616 61.2 61.2 61.2
About the same 315 31.3 31.3 92.9
Less accurate 34 3.4 3.4 95.9
Don't know / No comment 41 4.1 4.1 100.0
Total 1006 100.0 100.0
Base: All Active Respondents
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
45 May 2010
Table 17: Age group of the respondents (Q17)
Frequency Percent Valid Percent Cumulative Percent
Valid 15-17 67 6.6 6.6 6.8
18-19 38 3.8 3.8 10.4
20-29 176 17.5 17.5 27.9
30-39 222 22.0 22.0 49.9
40-49 264 26.2 26.2 76.1
50-59 192 19.0 19.0 95.1
60-64 49 4.9 4.9 100.0
Total 1008 100.0 100.0
Base: All respondents
Table 18: Education attainment of the respondents (Q18)
Frequency Percent Valid Percent
Cumulative
Percent
Valid No formal
schooling/kindergarten 7 0.7 0.7 0.7
Primary 81 8.0 8.0 8.7
Junior secondary (Form 1 to
Form 3) 106 10.5 10.5 19.2
Senior secondary (Form 4 to
Form 5)/Springboard Project 392 38.9 38.9 58.1
Matriculation (Form 6 to Form
7)/Technical College 93 9.2 9.2 67.4
Tertiary (non-degree or
associate degree) 108 10.7 10.7 78.1
Bachelor Degree 185 18.4 18.4 96.4
Master or Doctor Degree 29 2.9 2.9 99.3
Refuse to answer 7 0.7 0.7 100.0
Total 1008 100.0 100.0
Base: All respondents
Table 19: Occupation of the respondents (Q19)
Frequency Percent
Valid
Percent
Cumulative
Percent
Valid Student 158 15.7 15.7 15.7
Homemaker 197 19.5 19.5 35.2
Job seeker / unemployed 41 4.1 4.1 39.3
Retired 66 6.5 6.5 45.8
Professionals or associate professionals 110 10.9 10.9 56.7
Managers or administrators 58 5.8 5.8 62.5
Clerical staff 151 15.0 15.0 77.5
Technical staff 55 5.5 5.5 82.9
Non-technical staff 28 2.8 2.8 85.7
Service or sales staff 75 7.4 7.4 93.2
Self-employed 56 5.6 5.6 98.7
Refuse to answer 13 1.3 1.3 100.0
Total 1008 100.0 100.0
Base: All respondents
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
46 May 2010
Table 20: Industry of the respondents (Q20)
Frequency Percent Valid Percent
Cumulative
Percent
Valid Agriculture and Fishing 1 0.2 0.2 0.2
Manufacturing 39 7.1 7.1 7.3
Electricity, Gas and Water 7 1.3 1.3 8.6
Construction 50 9.2 9.2 17.8
Wholesale, Retail and
Import/Export Trades,
Restaurants and Hotels
115 21.1 21.1 38.8
Transport, Storage and
Communication 55 10.1 10.1 48.9
Financing, Insurance, Real
Estate and Business Services 97 17.8 17.8 66.7
Community, Social and
Personal Services 159 29.1 29.1 95.8
Refuse to answer 23 4.2 4.2 100.0
Total 546 100.0 100.0
Base: All working respondents
Table 21: Personal monthly income of the respondents (Q21)
Frequency Percent Valid Percent
Cumulative
Percent
Valid No income 87 8.6 8.6 8.6
$1-3,999 175 17.4 17.4 26.0
$4,000-9,999 182 18.1 18.1 44.0
$10,000-14,999 171 17.0 17.0 61.0
$15,000-19,999 113 11.2 11.2 72.2
$20,000-29,999 101 10.0 10.0 82.2
$30,000-39,999 42 4.2 4.2 86.4
$40,000 or above 51 5.1 5.1 91.5
Refuse to answer 86 8.5 8.5 100.0
Total 1008 100.0 100.0
Base: All respondents
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
47 May 2010
Table 22: Household monthly income of the respondents (Q22)
Frequency Percent Valid Percent
Cumulative
Percent
Valid No income 8 0.8 0.8 0.8
$1-12,499 104 10.3 10.3 11.1
$12,500-19,999 171 17.0 17.0 28.1
$20,000-29,999 181 18.0 18.0 46.0
$30,000-39,999 137 13.6 13.6 59.6
$40,000-49,999 91 9.0 9.0 68.7
$50,000-59,999 62 6.2 6.2 74.8
$60,000-69,999 13 1.3 1.3 76.1
$70,000 or above 60 6.0 6.0 82.0
Refuse to answer 181 18.0 18.0 100.0
Total 1008 100.0 100.0
Base: All respondents
Table 23: Gender of the respondents (Q23)
Frequency Percent Valid Percent Cumulative Percent
Valid Male 459 45.5 45.5 45.5
Female 549 54.5 54.5 100.0
Total 1008 100.0 100.0
Base: All respondents
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
48 May 2010
Appendix IV: Survey Data Analysis (Cross Tabulation
and Statistical Test Results)
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
49 May 2010
A4.1 Relationship between Respondents’ Demographics and Their Habit of
Reading, Watching or Listening to Weather Reports
Table 24: Relationship between respondents’ age and their habit of reading, watching or listening to
weather reports
Habit of reading, watching or listening to weather reports Total
Yes No
Count Row % Count Row % Count Row %
15-17 67 98.5% -- -- 67 100.0%
18-19 38 100.0% -- -- 38 100.0%
20-29 176 100.0% -- -- 176 100.0%
30-39 221 99.5% 1 0.5% 222 100.0%
40-49 263 99.6% 1 0.4% 264 100.0%
50-59 192 100.0% -- -- 192 100.0%
60-64 49 100.0% -- -- 49 100.0%
Total 1006 99.8.0% 1 0.2% 1005 100.0%
Fisher’s exact test: test statistic = 13.793, p-value = 0.032
Table 25: Relationship between respondents’ education attainment and their habit of reading,
watching or listening to weather reports
Habit of reading, watching or listening to weather
reports Total
Yes No
Count Row % Count Row % Count Row %
No formal
schooling/kindergarten 6 85.7% 1 14.3% 7 100.0%
Primary 81 100.0% -- -- 81 100.0%
Junior secondary
(Form 1 to Form 3) 106 100.0% -- -- 106 100.0%
Senior secondary
(Form 4 to Form
5)/Springboard Project
392 100.0% -- -- 392 100.0%
Matriculation (Form 6
to Form 7)/Technical
College
93 100.0% -- -- 93 100.0%
Tertiary (non-degree
or associate degree) 108 100.0% -- -- 108 100.0%
Bachelor Degree 184 99.5% 1 0.5% 185 100.0%
Master or Doctor
Degree 29 100.0% -- -- 29 100.0%
Total 999 99.8% 2 0.2% 1001 100.0%
Fisher’s exact test: test statistic = 1.688, p-value = 0.975
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
50 May 2010
Table 26: Relationship between respondents’ employment status and their habit of reading, watching
or listening to weather reports
Habit of reading, watching or listening to weather reports Total
Yes No
Count Row % Count Row % Count Row %
Yes 532 99.8% 1 0.2% 533 100.0%
No 461 99.8% 1 0.2% 462 100.0%
Total 993 99.9% 2 0.2% 995 100.0%
Fisher’s exact test: test statistic = 0.909, p-value = 0.340
Table 27: Relationship between respondents’ occupation and their habit of reading, watching or
listening to weather reports
Habit of reading, watching or listening to weather
reports Total
Yes No
Count Row % Count Row % Count Row %
Student 158 100.0% -- -- 158 100.0%
Homemaker 196 100.0% 1 0.5% 197 100.0%
Job seeker /
unemployed 41 100.0% -- -- 41 100.0%
Retired 66 100.0% -- -- 66 100.0%
Professionals or
associate
professionals
110 100.0% -- -- 110 100.0%
Managers or
administrators 58 100.0% -- -- 58 100.0%
Clerical staff 151 100.0% -- -- 151 100.0%
Technical staff 55 100.0% -- -- 55 100.0%
Non-technical staff 28 100.0% -- -- 28 100.0%
Service or sales staff 74 100.0% 1 1.3% 75 100.0%
Self-employed 56 100.0% -- -- 65 100.0%
Total 993 99.9% 2 0.2% 995 100.0%
Fisher’s exact test: test statistic = 5.103, p-value = 0.884
Table 28: Relationship between respondents’ gender and their habit of reading, watching or listening
to weather reports
Habit of reading, watching or listening to weather reports Total
Yes No
Count Row % Count Row % Count Row %
Male 459 100.0% -- -- 459 100.0%
Female 547 99.6% 2 0.4% 549 100.0%
Total 1006 99.8% 2 0.2% 1008 100.0%
Fisher’s exact test: test statistic = 1.225, p-value = 0.268
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
51 May 2010
A4.2 Relationship between Respondents’ Demographics and the Number of
Channels to access Weather Reports
Table 29: Relationship between respondents’ age and the number of channels used to access weather
reports
No. of Channels used
Age group Correlation Coefficient -.059
Sig. (2-tailed) .060
Count 1006
Spearman's rho test: r = -0.059, p-value = 0.060
Table 30: Relationship between respondents’ education attainment and the number of channels used
to access weather reports
No. of Channels used
Education attainment Correlation Coefficient .105(**)
Sig. (2-tailed) .001
Count 999
Spearman's rho test: r = 0.105, p-value = 0.001
** Correlation is significant at the 0.01 level (2-tailed).
Table 31: Relationship between respondents’ employment status and the number of channels used to
access weather reports
Employment status Count Mean Std. Deviation
No 461 2.0317 .73433
Yes 532 1.9442 .74153
Total 993 1.9859 .73903
Mann-Whitney U test: p-value = 0.062
Table 32: Relationship between non-working respondents’ occupation and the number of channels
used to access weather reports
Employment status Count Mean Std. Deviation Minimum Maximum
Student 158 2.3797 .66397 1.00 3.00
Homemaker 196 2.3265 .75482 1.00 3.00
Job seeker / unemployed 41 2.3659 .73335 1.00 3.00
Retired 66 2.1212 .83233 1.00 3.00
Total 461 2.3189 .73740 1.00 3.00
Kruskal Wallis test: test statistics = 11.478, p-value = 0.009
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
52 May 2010
Table 33: Relationship between working respondents’ occupation and the number of channels used to
access weather reports
Employment status Count Mean Std. Deviation Minimum Maximum
Professionals or associate
professionals 110 2.4273 .62749 1.00 3.00
Managers or administrators 58 2.4310 .65191 1.00 3.00
Clerical staff 151 2.4106 .63531 1.00 3.00
Technical staff 55 2.4727 .63405 1.00 3.00
Non-technical staff 28 2.2500 .75154 1.00 3.00
Service or sales staff 74 2.3649 .71336 1.00 3.00
Self-employed 56 2.3929 .67900 1.00 3.00
Total 532 2.4060 .65570 1.00 3.00
Kruskal Wallis test: test statistics = 12.377, p-value = 0.054
Table 34: Relationship between working respondents’ industry and the number of channels used to
access weather reports
Industry Count Mean Std. Deviation Minimum Maximum
Agriculture and Fishing 1 3.0000 . 3.00 3.00
Manufacturing 39 2.3333 .66227 1.00 3.00
Electricity, Gas and Water 7 2.2857 .48795 2.00 3.00
Construction 50 2.5200 .61412 1.00 3.00
Wholesale, Retail and
Import/Export Trades,
Restaurants and Hotels
114 2.3246 .71017 1.00 3.00
Transport, Storage and
Communication 55 2.4364 .66007 1.00 3.00
Financing, Insurance, Real
Estate and Business Services 97 2.4536 .61272 1.00 3.00
Community, Social and
Personal Services 159 2.4088 .66764 1.00 3.00
Total 522 2.4061 .65848 1.00 3.00
Kruskal Wallis test: test statistics = 6.496, p-value = 0.483
Table 35: Relationship between respondents’ personal monthly income and the number of channels
used to access weather reports
No. of Channels used
Personal monthly income Correlation Coefficient .056
Sig. (2-tailed) .087
Count 921
Spearman's rho test: r = 0.056, p-value = 0.087
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
53 May 2010
Table 36: Relationship between respondents’ household monthly income and the number of channels
used to access weather reports
No. of Channels used
Household monthly income Correlation Coefficient .102(**)
Sig. (2-tailed) .003
Count 826
Spearman's rho test: r = 0.102, p-value = 0.003
** Correlation is significant at the 0.01 level (2-tailed).
Table 37: Relationship between respondents’ gender and the number of channels used to access
weather reports
Gender Count Mean Std. Deviation Minimum Maximum
Male 459 2.3508 .68440 1.00 3.00
Female 547 2.3766 .70636 1.00 3.00
Total 1006 2.3648 .69620 1.00 3.00
Mann-Whitney U test: p-value = 0.208
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
54 May 2010
A4.3 Relationship between Respondents’ Demographics and Their Perception of
Accuracy on Weather Forecasts over the Past Several Months
Table 38: Relationship between respondents’ age and their perception of accuracy on weather
forecasts over the past several months
Perception of accuracy on weather
forecasts over the past several months
Age group Correlation Coefficient .217(**)
Sig. (2-tailed) .000
Count 1005
Spearman's rho test: r = 0.217, p-value = 0.000
** Correlation is significant at the 0.01 level (2-tailed).
Table 39: Relationship between respondents’ education attainment and their perception of accuracy
on weather forecasts over the past several months
Perception of accuracy on weather
forecasts over the past several months
Education attainment Correlation Coefficient -.083(**)
Sig. (2-tailed) .009
Count 998
Spearman's rho test: r = -0.083, p-value = 0.009
** Correlation is significant at the 0.01 level (2-tailed).
Table 40: Relationship between respondents’ employment status and their perception of accuracy on
weather forecasts over the past several months
Employment status Count Mean Std. Deviation Minimum Maximum
No 460 3.8652 .69490 Very inaccurate Very accurate
Yes 532 3.9248 .72225 Very inaccurate Very accurate
Total 992 3.8972 .70996 Very inaccurate Very accurate
Mann-Whitney U test: p-value = 0.162
Table 41: Relationship between non-working respondents’ occupation and their perception of
accuracy on weather forecasts over the past several months
Occupation Count Mean Std. Deviation Minimum Maximum
Student 157 3.7261 .70358 Very
inaccurate
Very
accurate
Homemaker 196 3.8878 .72157 Very
inaccurate
Very
accurate
Job seeker / unemployed 41 3.9024 .58330 Somewhat
inaccurate
Very
accurate
Retired 66 4.1061 .58517 Somewhat
inaccurate
Very
accurate
Total 460 3.8652 .69490 Very
inaccurate
Very
accurate
Kruskal Wallis test: test statistics = 9.338, p-value = 0.025
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
55 May 2010
Table 42: Relationship between working respondents’ occupation and their perception of accuracy on
weather forecasts over the past several months
Occupation Count Mean Std. Deviation Minimum Maximum
Professionals or associate
professionals 110 3.9364 .68103
Very
inaccurate
Very
accurate
Managers or administrators 58 3.9310 .83481
Very
inaccurate
Very
accurate
Clerical staff 151 3.8543 .76068
Very
inaccurate
Very
accurate
Technical staff 55 3.9273 .71633
Somewhat
inaccurate
Very
accurate
Non-technical staff 28 3.9286 .60422 Average
Very
accurate
Service or sales staff 74 3.9054 .62305
Somewhat
inaccurate
Very
accurate
Self-employed 56 4.1071 .75507
Somewhat
inaccurate
Very
accurate
Total 532 3.9248 .72225
Very
inaccurate
Very
accurate
Kruskal Wallis test: test statistics = 6.816, p-value = 0.338
Table 43: Relationship between working respondents’ industry and their perception of accuracy on
weather forecasts over the past several months
Industry Count Mean Std. Deviation Minimum Maximum
Agriculture and Fishing 1 3.0000 . Average Average
Manufacturing 39 3.8462 .53991 Average
Very
accurate
Electricity, Gas and Water 7 4.1429 .69007 Average
Very
accurate
Construction 50 4.1000 .61445 Average
Very
accurate
Wholesale, Retail and
Import/Export Trades,
Restaurants and
114 3.9649 .70309 Somewhat
inaccurate
Very
accurate
Transport, Storage and
Communication 55 3.8364 .83364
Very
inaccurate
Very
accurate
Financing, Insurance, Real
Estate and Business Services 97 3.7938 .80284
Very
inaccurate
Very
accurate
Community, Social and
Personal Services 159 3.9686 .69739
Somewhat
inaccurate
Very
accurate
Total 522 3.9253 .72000
Very
inaccurate
Very
accurate
Kruskal Wallis test: test statistics = 2.605, p-value = 0.919
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
56 May 2010
Table 44: Relationship between respondents’ personal monthly income and their perception of
accuracy on weather forecasts over the past several months
Perception of accuracy on
weather forecasts over the
past several months
Personal monthly income Correlation Coefficient .094(**)
Sig. (2-tailed) .004
Count 920
Spearman's rho test: r = 0.094, p-value = 0.004
** Correlation is significant at the 0.01 level (2-tailed).
Table 45: Relationship between respondents’ household monthly income and their perception of
accuracy on weather forecasts over the past several months
Perception of accuracy on
weather forecasts over the
past several months
Household monthly income Correlation Coefficient .046(*)
Sig. (2-tailed) .186
Count 826
Spearman's rho test: r = 0.046, p-value = 0.186
* Correlation is significant at the 0.05 level (2-tailed).
Table 46: Relationship between respondents’ gender and their perception of accuracy on weather
forecasts over the past several months
Gender Count Mean Std. Deviation Minimum Maximum
Male 458 3.9476 .69500 Very inaccurate Very accurate
Female 547 3.8483 .72173 Very inaccurate Very accurate
Total 1005 3.8935 .71105 Very inaccurate Very accurate
Mann-Whitney U test: p-value = 0.806
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
57 May 2010
A4.4 Relationship between Respondents’ Demographics and the Percentage of
Accurate Weather Forecasts over the Past Several Months
Table 47: Relationship between respondents’ age and the percentage of accurate weather forecasts
over the past several months
Percentage of accurate weather
forecasts over the past several months
Age group Correlation Coefficient .217(**)
Sig. (2-tailed) .000
Count 1001
Spearman's rho test: r = 0.217, p-value = 0.000
** Correlation is significant at the 0.01 level (2-tailed).
Table 48: Relationship between respondents’ education attainment and the percentage of accurate
weather forecasts over the past several months
Percentage of accurate weather
forecasts over the past several months
Education attainment Correlation Coefficient -.104(**)
Sig. (2-tailed) .001
Count 994
Spearman's rho test: r = -0.104, p-value = 0.001
** Correlation is significant at the 0.01 level (2-tailed).
Table 49: Relationship between respondents’ employment status and the percentage of accurate
weather forecasts over the past several months
Employment status N Mean Std. Deviation Minimum Maximum
No 458 78.0568 12.61642 10.00 100.00
Yes 530 78.3736 12.52929 5.00 100.00
Total 988 78.2267 12.56437 5.00 100.00
Mann-Whitney U test: p-value = 0.110
Table 50: Relationship between non-working respondents’ occupation and the percentage of accurate
weather forecasts over the past several months
Occupation N Mean Std. Deviation Minimum Maximum
Student 157 75.5605 13.58465 10.00 98.00
Homemaker 194 78.6392 12.68158 20.00 100.00
Job seeker / unemployed 41 79.0244 10.73659 30.00 90.00
Retired 66 81.6818 9.88730 50.00 100.00
Total 458 78.0568 12.61642 10.00 100.00
Kruskal Wallis test: test statistics = 19.515, p-value = 0.000
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
58 May 2010
Table 51: Relationship between working respondents’ occupation and the percentage of accurate
weather forecasts over the past several months
Occupation N Mean Std. Deviation Minimum Maximum
Professionals or associate
professionals 110 78.5182 10.42996 40.00 95.00
Managers or administrators 57 79.8596 11.72823 50.00 98.00
Clerical staff 151 77.2384 13.59201 10.00 100.00
Technical staff 55 77.8182 12.42621 40.00 95.00
Non-technical staff 28 81.3571 7.12956 70.00 98.00
Service or sales staff 73 77.7123 14.31926 5.00 100.00
Self-employed 56 79.5536 13.88252 30.00 100.00
Total 530 78.3736 12.52929 5.00 100.00
Kruskal Wallis test: test statistics = 3.161, p-value = 0.788
Table 52: Relationship between working respondents’ industry and the percentage of accurate
weather forecasts over the past several months
Industry Count Mean Std. Deviation Minimum Maximum
Agriculture and Fishing 1 50.0000 . 50.00 50.00
Manufacturing 39 79.4872 10.86974 40.00 100.00
Electricity, Gas and Water 7 85.0000 10.34408 70.00 99.00
Construction 50 81.2600 10.02000 50.00 100.00
Wholesale, Retail and
Import/Export Trades,
Restaurants and Hotels
113 77.9381 13.48695 5.00 99.00
Transport, Storage and
Communication 55 75.6909 13.17809 40.00 98.00
Financing, Insurance, Real
Estate and Business Services 96 77.0833 13.15228 10.00 95.00
Community, Social and
Personal Services 159 79.0881 12.03128 40.00 100.00
Total 520 78.3712 12.51907 5.00 100.00
Kruskal Wallis test: test statistics = 5.307, p-value = 0.623
Table 53: Relationship between respondents’ personal monthly income and the percentage of
accurate weather forecasts over the past several months
Percentage of accurate weather
forecasts over the past several months
Personal monthly income Correlation Coefficient .042
Sig. (2-tailed) .202
Count 916
Spearman's rho test: r = 0.042, p-value = 0.202
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
59 May 2010
Table 54: Relationship between respondents’ household monthly income and the percentage of
accurate weather forecasts over the past several months
Percentage of accurate weather
forecasts over the past several months
Household monthly income Correlation Coefficient .007
Sig. (2-tailed) .841
Count 821
Spearman's rho test: r = 0.007, p-value = 0.841
Table 55: Relationship between respondents’ gender and the percentage of accurate weather
forecasts over the past several months
Gender Count Mean Std. Deviation Minimum Maximum
Male 458 78.2838 12.86209 5.00 100.00
Female 543 78.0368 12.35045 20.00 100.00
Total 1001 78.1499 12.58140 5.00 100.00
Mann-Whitney U test: p-value = 0.059
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
60 May 2010
A4.5 Relationship between Respondents’ Demographics and Their Perception of
Accuracy on Different Aspects of Weather Forecasts over the Past Several Months
Table 56: Relationship between respondents’ age and their perception of accuracy on different
aspects of weather forecasts over the past several months
Perception of accuracy on different aspects of weather forecasts
over the past several months
Temperature Fine / Cloudy Rain storm Typhoon
Age group Correlation Coefficient .164(**) .132(**) .118(**) .059
Sig. (2-tailed) .000 .000 .000 .073
Count 1002 991 995 925
Remark: Spearman's rho test
** Correlation is significant at the 0.01 level (2-tailed).
Table 57: Relationship between respondents’ education attainment and their perception of accuracy
on different aspects of weather forecasts over the past several months
Perception of accuracy on different aspects of weather forecasts
over the past several months
Temperature Fine / Cloudy Rain storm Typhoon
Education
attainment
Correlation Coefficient -.049 -.083(**) -.054 -.067(**)
Sig. (2-tailed) .123 .009 .099 .042
Count 996 984 948 918
Remark: Spearman's rho test
** Correlation is significant at the 0.01 level (2-tailed).
Table 58: Relationship between respondents’ employment status and their perception of accuracy on
different aspects of weather forecasts over the past several months
Employment status Count Mean Std. Deviation
Temperature No 460 3.2522 .61348
Yes 530 3.3283 .63137
Total 990 3.2929 .62397
Fine / Cloudy No 454 3.2533 .71235
Yes 524 3.2443 .71415
Total 978 3.2485 .71296
Rain storm No 434 3.2120 .74527
Yes 508 3.2717 .71406
Total 942 3.2442 .72882
Typhoon No 421 3.3848 .68602
Yes 491 3.4114 .68645
Total 912 3.3991 .68601
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
61 May 2010
Table 59: Relationship between non-working respondents’ occupation and their perception of
accuracy on different aspects of weather forecasts over the past several months
Occupation Count Mean Std. Deviation
Temperature Student 158 3.1203 .64203
Homemaker 196 3.3010 .57841
Job seeker / unemployed 41 3.1951 .67895
Retired 65 3.4615 .53259
Total 460 3.2522 .61348
Fine / Cloudy Student 153 3.1895 .76736
Homemaker 195 3.2564 .67036
Job seeker / unemployed 40 3.2250 .69752
Retired 66 3.4091 .70115
Total 454 3.2533 .71235
Rain storm Student 148 3.1081 .78363
Homemaker 187 3.1872 .73488
Job seeker / unemployed 37 3.3514 .71555
Retired 62 3.4516 .64471
Total 434 3.2120 .74527
Typhoon Student 143 3.3636 .70756
Homemaker 182 3.4011 .68818
Job seeker / unemployed 35 3.3714 .77024
Retired 61 3.3934 .58534
Total 421 3.3848 .68602
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
62 May 2010
Table 60: Relationship between working respondents’ occupation and their perception of accuracy on
different aspects of weather forecasts over the past several months
Occupation Count Mean Std. Deviation
Temperature Professionals or associate professionals 110 3.3273 .63692
Managers or administrators 58 3.4310 .62442
Clerical staff 151 3.3113 .62381
Technical staff 55 3.2909 .71162
Non-technical staff 28 3.2500 .58531
Service or sales staff 74 3.2838 .63073
Self-employed 54 3.4074 .59932
Total 530 3.3283 .63137
Fine / Cloudy
Professionals or associate professionals 108 3.3241 .62396
Managers or administrators 58 3.1897 .78264
Clerical staff 150 3.1400 .76877
Technical staff 54 3.3148 .69565
Non-technical staff 27 3.4074 .63605
Service or sales staff 73 3.2329 .73637
Self-employed 54 3.2963 .66246
Total 524 3.2443 .71415
Rain storm Professionals or associate professionals 106 3.2358 .75026
Managers or administrators 54 3.3889 .68451
Clerical staff 143 3.2797 .69612
Technical staff 54 3.0556 .76273
Non-technical staff 25 3.5600 .50662
Service or sales staff 73 3.2055 .70630
Self-employed 53 3.3774 .71324
Total 508 3.2717 .71406
Typhoon Professionals or associate professionals 102 3.4216 .63614
Managers or administrators 51 3.3529 .74360
Clerical staff 137 3.3504 .70284
Technical staff 52 3.4038 .69338
Non-technical staff 27 3.5185 .70002
Service or sales staff 71 3.4930 .58244
Self-employed 51 3.4510 .80781
Total 491 3.4114 .68645
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
63 May 2010
Table 61: Relationship between respondents’ personal monthly income and their perception of
accuracy on different aspects of weather forecasts over the past several months
Perception of accuracy on different aspects of weather forecasts
over the past several months
Temperature Fine / Cloudy Rain storm Typhoon
Personal
monthly
income
Correlation Coefficient .080(*) .023 .067(*) .033
Sig. (2-tailed) .015 .492 .047 .334
Count 919 922 875 849
Remark: Spearman's rho test
* Correlation is significant at the 0.05 level (2-tailed).
Table 62: Relationship between respondents’ household monthly income and their perception of
accuracy on different aspects of weather forecasts over the past several months
Perception of accuracy on different aspects of weather forecasts
over the past several months
Temperature Fine / Cloudy Rain storm Typhoon
Household
monthly
income
Correlation Coefficient -.010 -.023 .018 -.017
Sig. (2-tailed) .773 .516 .608 .647
Count 824 813 785 762
Remark: Spearman's rho test
Table 63: Relationship between respondents’ gender and their perception of accuracy on different
aspects of weather forecasts over the past several months
Gender Count Mean Std. Deviation
Temperature Male 457 3.3239 .64900
Female 545 3.2697 .60231
Total 1002 3.2944 .62431
Fine / Cloudy Male 451 3.3038 .70771
Female 540 3.2037 .71246
Total 991 3.2492 .71169
Rain storm Male 442 3.2647 .73158
Female 513 3.2242 .72514
Total 955 3.2429 .72803
Typhoon Male 424 3.3868 .70889
Female 501 3.3992 .66657
Total 925 3.3935 .68595
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
64 May 2010
A4.6 Relationship between Respondents’ Demographics and Their Perception of Accuracy on Current Weather Forecasts as Compared with Those 3 to 4 Years ago
Table 64: Relationship between respondents’ age and Their Perception of Accuracy on Current
Weather Forecasts as Compared with Those 3 to 4 Years ago
Their Perception of Accuracy on Current Weather Forecasts as
Compared with Those 3 to 4 Years ago
Age group Correlation Coefficient .299(**)
Sig. (2-tailed) .000
Count 975
Spearman's rho test: r = 0.299, p-value = 0.000
** Correlation is significant at the 0.01 level (2-tailed).
Table 65: Relationship between respondents’ education attainment and Their Perception of Accuracy
on Current Weather Forecasts as Compared with Those 3 to 4 Years ago
Their Perception of Accuracy on Current Weather
Forecasts as Compared with Those 3 to 4 Years ago
Education attainment Correlation Coefficient -.134(**)
Sig. (2-tailed) .000
Count 969
Spearman's rho test: r = -0.134, p-value = 0.000
** Correlation is significant at the 0.01 level (2-tailed).
Table 66: Relationship between respondents’ employment status and Their Perception of Accuracy on
Current Weather Forecasts as Compared with Those 3 to 4 Years ago
Employment status Count Mean Std. Deviation Minimum Maximum
No 442 2.5814 .61273 Less accurate More accurate
Yes 521 2.6296 .60368 Less accurate More accurate
Total 963 2.6075 .60801 Less accurate More accurate
Mann-Whitney U test: p-value = 0.580
Table 67: Relationship between non-working respondents’ occupation and Their Perception of
Accuracy on Current Weather Forecasts as Compared with Those 3 to 4 Years ago
Occupation Count Mean
Std.
Deviation Minimum Maximum
Student 154 2.3766 .65756 Less accurate More accurate
Homemaker 183 2.6612 .59759 Less accurate More accurate
Job seeker / unemployed 40 2.6750 .57233 Less accurate More accurate
Retired 65 2.7846 .41429 Less accurate More accurate
Total 442 2.5814 .61273 Less accurate More accurate
Kruskal Wallis test: test statistics = 25.895 p-value = 0.000
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
65 May 2010
Table 68: Relationship between working respondents’ occupation and Their Perception of Accuracy
on Current Weather Forecasts as Compared with Those 3 to 4 Years ago
Occupation Count Mean Std. Deviation Minimum Maximum
Professionals or associate
professionals 109 2.5321 .67452
Less
accurate
More
accurate
Managers or administrators 57 2.5965 .62277 Less
accurate
More
accurate
Clerical staff 145 2.6345 .58706 Less
accurate
More
accurate
Technical staff 53 2.6226 .62716 Less
accurate
More
accurate
Non-technical staff 28 2.8214 .39002 Less
accurate
More
accurate
Service or sales staff 73 2.6027 .63987 Less
accurate
More
accurate
Self-employed 56 2.7857 .45584 Less
accurate
More
accurate
Total 521 2.6296 .60368 Less
accurate
More
accurate
Kruskal Wallis test: test statistics = 4.991, p-value = 0.545
Table 69: Relationship between working respondents’ industry and Their Perception of Accuracy on
Current Weather Forecasts as Compared with Those 3 to 4 Years ago
Industry Count Mean Std. Deviation Minimum Maximum
Manufacturing 39 2.6923 .56911 Less
accurate
More
accurate
Electricity, Gas and Water 7 2.8571 .37796 About the
same
More
accurate
Construction 49 2.6327 .56620 Less
accurate
More
accurate
Wholesale, Retail and
Import/Export Trades,
Restaurants and Hotels
113 2.6637 .57648 Less
accurate
More
accurate
Transport, Storage and
Communication 53 2.6604 .58650
Less
accurate
More
accurate
Financing, Insurance, Real
Estate and Business Services 94 2.5745 .66380
Less
accurate
More
accurate
Community, Social and
Personal Services 156 2.5962 .63020
Less
accurate
More
accurate
Total 511 2.6282 .60610 Less
accurate
More
accurate
Kruskal Wallis test: test statistics = 9.763, p-value = 0.202
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
66 May 2010
Table 70: Relationship between respondents’ personal monthly income and Their Perception of
Accuracy on Current Weather Forecasts as Compared with Those 3 to 4 Years ago
Their Perception of Accuracy on Current
Weather Forecasts as Compared with
Those 3 to 4 Years ago
Personal monthly income Correlation Coefficient .084(*)
Sig. (2-tailed) .012
Count 894
Spearman's rho test: r = 0.084, p-value = 0.012
* Correlation is significant at the 0.05 level (2-tailed).
Table 71: Relationship between respondents’ household monthly income and Their Perception of
Accuracy on Current Weather Forecasts as Compared with Those 3 to 4 Years ago
Their Perception of Accuracy on Current
Weather Forecasts as Compared with Those 3 to
4 Years ago
Household monthly income Correlation Coefficient -.007
Sig. (2-tailed) .836
Count 805
Spearman's rho test: r = -0.007, p-value = 0.836
Table 72: Relationship between respondents’ gender and Their Perception of Accuracy on Current
Weather Forecasts as Compared with Those 3 to 4 Years ago
Gender Count Mean Std. Deviation Minimum Maximum
Male 449 2.6058 .57714 Less accurate More accurate
Female 526 2.6103 .63111 Less accurate More accurate
Total 975 2.6082 .60655 Less accurate More accurate
Mann-Whitney U test: p-value = 0.181
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
67 May 2010
A4.7 Relationship between Respondents’ Demographics and Their Perception of
Overall Satisfaction on Services provided by Hong Kong Observatory over the Past
Several Months
Table 73: Relationship between respondents’ age and Their Perception of Overall Satisfaction on
Services provided by Hong Kong Observatory over the Past Several Months
Perception of Overall Satisfaction on Services provided by
Hong Kong Observatory over the Past Several Months
Age group Correlation Coefficient .260(**)
Sig. (2-tailed) .000
Count 1005
Spearman's rho test: r = 0.260, p-value = 0.000
** Correlation is significant at the 0.01 level (2-tailed).
Table 74: Relationship between respondents’ education attainment and Their Perception of Overall
Satisfaction on Services provided by Hong Kong Observatory over the Past Several Months
Perception of Overall Satisfaction on Services provided by
Hong Kong Observatory over the Past Several Months
Education attainment Correlation Coefficient -.136(**)
Sig. (2-tailed) .000
Count 998
Spearman's rho test: r = -0.136, p-value = 0.000
** Correlation is significant at the 0.01 level (2-tailed).
Table 75: Relationship between respondents’ employment status and Their Perception of Overall
Satisfaction on Services provided by Hong Kong Observatory over the Past Several Months
Employment status Count Mean Std. Deviation Minimum Maximum
No 461 7.7440 1.33985 1.00 10.00
Yes 531 7.8079 1.28885 2.00 10.00
Total 992 7.7782 1.31252 1.00 10.00
Mann-Whitney U test: p-value = 0.064
Table 76: Relationship between non-working respondents’ occupation and Their Perception of Overall
Satisfaction on Services provided by Hong Kong Observatory over the Past Several Months
Occupation Count Mean
Std.
Deviation Minimum Maximum
Student 158 7.4114 1.33130 1.00 10.00
Homemaker 196 7.8673 1.37477 2.00 10.00
Job seeker / unemployed 41 7.7805 1.19399 5.00 10.00
Retired 66 8.1515 1.17986 4.00 10.00
Total 461 7.7440 1.33985 1.00 10.00
Kruskal Wallis test: test statistics = 22.764, p-value = 0.000
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
68 May 2010
Table 77: Relationship between working respondents’ occupation and Their Perception of Overall
Satisfaction on Services provided by Hong Kong Observatory over the Past Several Months
Occupation Count Mean Std. Deviation Minimum Maximum
Professionals or associate
professionals 110 7.8364 1.00938 5.00 10.00
Managers or administrators 58 7.7414 1.23630 4.00 10.00
Clerical staff 151 7.6821 1.27735 5.00 10.00
Technical staff 54 8.0926 1.13717 5.00 10.00
Non-technical staff 28 7.9286 1.46385 5.00 10.00
Service or sales staff 74 7.7297 1.48321 3.00 10.00
Self-employed 56 7.9286 1.60519 2.00 10.00
Total 531 7.8079 1.28885 2.00 10.00
Kruskal Wallis test: test statistics = 9.566, p-value = 0.144
Table 78: Relationship between working respondents’ industry and Their Perception of Overall
Satisfaction on Services provided by Hong Kong Observatory over the Past Several Months
Industry Count Mean Std. Deviation Minimum Maximum
Agriculture and Fishing 1 8.0000 . 8.00 8.00
Manufacturing 38 7.9737 1.10250 5.00 10.00
Electricity, Gas and Water 7 8.0000 1.00000 7.00 10.00
Construction 50 8.0400 1.33951 5.00 10.00
Wholesale, Retail and
Import/Export Trades,
Restaurants and
114 7.6842 1.41619 3.00 10.00
Transport, Storage and
Communication 55 7.6909 1.21522 5.00 10.00
Financing, Insurance, Real
Estate and Business Services 97 7.7216 1.37494 2.00 10.00
Community, Social and
Personal Services 159 7.8868 1.18525 5.00 10.00
Total 521 7.8138 1.28373 2.00 10.00
Kruskal Wallis test: test statistics = 17.505, p-value = 0.014
Table 79: Relationship between respondents’ personal monthly income and Their Perception of
Overall Satisfaction on Services provided by Hong Kong Observatory over the Past Several Months
Perception of Overall Satisfaction on Services
provided by Hong Kong Observatory over the Past
Several Months
Personal monthly income Correlation Coefficient .057
Sig. (2-tailed) .084
Count 921
Spearman's rho test: r = 0.057, p-value = 0.084
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
69 May 2010
Table 80: Relationship between respondents’ household monthly income and Their Perception of
Overall Satisfaction on Services provided by Hong Kong Observatory over the Past Several Months
Perception of Overall Satisfaction on Services
provided by Hong Kong Observatory over the Past
Several Months
Household monthly income Correlation Coefficient -.009
Sig. (2-tailed) .800
Count 826
Spearman's rho test: r =- 0.009, p-value = 0.800
Table 81: Relationship between respondents’ gender and Their Perception of Overall Satisfaction on
Services provided by Hong Kong Observatory over the Past Several Months
Gender Count Mean Std. Deviation Minimum Maximum
Male 458 7.7686 1.28061 1.00 10.00
Female 547 7.7715 1.34684 2.00 10.00
Total 1005 7.7701 1.31642 1.00 10.00
Mann-Whitney U test: p-value = 0.393
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
70 May 2010
A4.8 Relationship between Respondents’ Demographics and Their Perception of
Accuracy on Current Tropical Cyclone Warning Services as Compared with Those 3
to 4 Years ago
Table 82: Relationship between respondents’ age and Their Perception of Accuracy on Current
Tropical Cyclone Warning Services as Compared with Those 3 to 4 Years ago
Their Perception of Accuracy on Current Tropical Cyclone
Warning Services as Compared with Those 3 to 4 Years ago
Age group Correlation Coefficient .241(**)
Sig. (2-tailed) .000
Count 965
Spearman's rho test: r = 0.241, p-value = 0.000
** Correlation is significant at the 0.01 level (2-tailed).
Table 83: Relationship between respondents’ education attainment and Their Perception of Accuracy
on Current Tropical Cyclone Warning Services as Compared with Those 3 to 4 Years ago
Their Perception of Accuracy on Current Tropical Cyclone
Warning Services as Compared with Those 3 to 4 Years ago
Education attainment Correlation Coefficient -.184(**)
Sig. (2-tailed) .000
Count 959
Spearman's rho test: r = -0.184, p-value = 0.000
** Correlation is significant at the 0.01 level (2-tailed).
Table 84: Relationship between respondents’ employment status and Their Perception of Accuracy on
Current Tropical Cyclone Warning Services as Compared with Those 3 to 4 Years ago
Employment status Count Mean Std. Deviation Minimum Maximum
No 440 2.6182 .53116 Less accurate More accurate
Yes 514 2.5914 .57600 Less accurate More accurate
Total 954 2.6038 .55564 Less accurate More accurate
Mann-Whitney U test: p-value = 0.064
Table 85: Relationship between non-working respondents’ occupation and Their Perception of
Accuracy on Current Tropical Cyclone Warning Services as Compared with Those 3 to 4 Years ago
Occupation Count Mean
Std.
Deviation Minimum Maximum
Student 153 2.4444 .56065 Less accurate More accurate
Homemaker 182 2.7143 .48822 Less accurate More accurate
Job seeker / unemployed 40 2.5750 .54948 Less accurate More accurate
Retired 65 2.7846 .45043 Less accurate More accurate
Total 440 2.6182 .53116 Less accurate More accurate
Kruskal Wallis test: test statistics = 22.764, p-value = 0.000
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
71 May 2010
Table 86: Relationship between working respondents’ occupation and Their Perception of Accuracy
on Current Tropical Cyclone Warning Services as Compared with Those 3 to 4 Years ago
Occupation Count Mean
Std.
Deviation Minimum Maximum
Professionals or associate
professionals 105 2.5524 .60417 Less accurate More accurate
Managers or administrators 56 2.6071 .52841 Less accurate More accurate
Clerical staff 144 2.5347 .59028 Less accurate More accurate
Technical staff 55 2.6364 .58890 Less accurate More accurate
Non-technical staff 26 2.6154 .63730 Less accurate More accurate
Service or sales staff 74 2.6351 .56312 Less accurate More accurate
Self-employed 54 2.6852 .50746 Less accurate More accurate
Total 514 2.5914 .57600 Less accurate More accurate
Kruskal Wallis test: test statistics = 9.566, p-value = 0.144
Table 87: Relationship between working respondents’ industry and Their Perception of Accuracy on
Current Tropical Cyclone Warning Services as Compared with Those 3 to 4 Years ago
Industry Count Mean
Std.
Deviation Minimum Maximum
Manufacturing 38 2.5263 .64669 Less accurate More accurate
Electricity, Gas and Water 7 2.5714 .53452 About the same More accurate
Construction 50 2.6200 .53031 Less accurate More accurate
Wholesale, Retail and
Import/Export Trades,
Restaurants and
109 2.5780 .59774 Less accurate More accurate
Transport, Storage and
Communication 54 2.4815 .63664 Less accurate More accurate
Financing, Insurance, Real
Estate and Business Services 92 2.6087 .51262 Less accurate More accurate
Community, Social and
Personal Services 154 2.6364 .56958 Less accurate More accurate
Total 504 2.5913 .57413 Less accurate More accurate
Kruskal Wallis test: test statistics = 17.505, p-value = 0.014
Table 88: Relationship between respondents’ personal monthly income and Their Perception of
Accuracy on Current Tropical Cyclone Warning Services as Compared with Those 3 to 4 Years ago
Perception of Overall Satisfaction on Services
provided by Hong Kong Observatory over the Past
Several Months
Personal monthly income Correlation Coefficient .037
Sig. (2-tailed) .267
Count 888
Spearman's rho test: r = 0.037, p-value = 0.267
Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010
72 May 2010
Table 89: Relationship between respondents’ household monthly income and Their Perception of
Accuracy on Current Tropical Cyclone Warning Services as Compared with Those 3 to 4 Years ago
Perception of Overall Satisfaction on Services
provided by Hong Kong Observatory over the Past
Several Months
Household monthly income Correlation Coefficient .004
Sig. (2-tailed) .903
Count 796
Spearman's rho test: r = 0.004, p-value = 0.903
Table 90: Relationship between respondents’ gender and Their Perception of Accuracy on Current
Tropical Cyclone Warning Services as Compared with Those 3 to 4 Years ago
Gender Count Mean Std. Deviation Minimum Maximum
Male 450 2.5778 .56193 Less accurate More accurate
Female 515 2.6252 .55210 Less accurate More accurate
Total 965 2.6031 .55692 Less accurate More accurate
Mann-Whitney U test: p-value = 0.393