Jignesh Final Report

7/28/2019 Jignesh Final Report

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A

Project Report

On

AGE GROUP INFLUENCE FACTOR FOR PURCHASING

INURANCE POLICY

Undertaken at:

HDFC STANDARD LIFE INSURANCE CO.LTD.

VALSAD

Submitted by:

JIGNESH P.YAGNIK

(07MBA60)

Guided by:

Mr. ANIL SARAOGI

MBA (2007-09)

SHRIMAD RAJCHANDRA INSTITUTE OF MANAGEMENT

AND COMPUTER APPLICATION


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ACKNOWLEDGEMENT

At this stage of my long educational journey, I look back and find that

though mine is a fairly sail, it has been memorizing extravagance of

memorable experience. At this gratifying moment of completion of my

research problem, I feel obliged to record my gratitude to those who

have helped me.

I wish to convey my special thanks to Mr. Jigar desai (Branch Manager)

and Mr. Digant desai (Sales Manager) at HDFC standard Life Insurance

co. Ltd., who has been a constant source of inspiration and

encouragement to me.

I feel immense pleasure in expressing my deep sense of respect and

indebtedness to my institute project guide, Mr.Anil saraogi, Faculty,

Shrimad Rajchandra Institute of Management & Computer application

(SRIMCA), Tarsadi for his valuable guidance throughout preparation of

this report.

I feel immense pleasure to thank Dr. B. C Patel, Director, Shrimad

Rajchandra Institute of Management & Computer application (SRIMCA),

Tarsadi for making available all facilities in fulfilling the requirements

for the research work. And I also thank those who helped me directly or

indirectly.

Jignesh p yagnik

(07MBA60)


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Executive Summary

Purpose:

The primary purpose is to study the factor which influences the

various age groups to buy the insurance policy.

The life insurance market in India is an underdeveloped market.

The penetration of life insurance products was 19 percent of the total

400 million of the insurable population.

Today, everyone in the world wants to secure their future. All

wants to eliminate the risk of uncertain life. So my study is to know

which factor influences various age groups to buy the insurance policy.

Design/Methodology/Approach:

The data has been collected through both primary and secondary

data collection methods. This project report includes secondary data

about the life insurance industry, company details, etc. Primary data

are collected through questionnaire filled by the respondents during

face to face interaction.

At the initial stage the research design is exploratory because

the research started with review of literature available on the Internet

and in books. Based on that, the final research statement was framed.

The subsequent research design is descriptive as it aims to describe

the factor which influences the various age groups to buy the

insurance policy.

Sampling design is non-probability and sampling method is

convenience sampling because of time and money constraints. The

sample size consisted of 160 respondents across the population.


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For the data analysis, various statistical tests like one sample t-

test, independent sample t test and measures of central tendencies

were applied through SPSS software.

Findings

1. 71.25% of respondents have given 1st rank to LIC; other

insurance companies have got very less frequency in

getting 1st rank. So we can say that LIC is at first position

in peoples mind.

2. 45.625% respondents preferred to invest in fix deposit.

3. 27% of respondent have unit linked endowment plan.

4. 95% of people prefer HDFC standard life to purchase new

policy.

5. 45% of people says that brand name influence them to

buy the policy.

6. For the age group of (18-25) return on investment is the

most important factor.

7. For the age group of (26-35) tax benefits is the most

important factor.

8. For the age group of (36-45) risk cover, transparency is

the most important factor.

9. For the age group of 46&above death benefit, withdrawal

option in the policy is the most important factor.

10. Total customer satisfaction index is 85%.

11. The policy holder are satisfied with risk cover ,tax benefits

safety ,transparency ,lock in period, withdrawal option in the

policy


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Table of content

Sr. No. Topic Page No.

1 INTRODUCTION

A. Industry profile

B. Company profile

2 RESEARCH METHODOLOGY

3 DATA ANALYSIS & INTERPRETATION

4 FINDINGS

5 CONCLUSIONS

6 RECOMMENDATIONS

7 BIBLIOGRAPHY

8 APPENDIX


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Ch-1 INTRODUCTION

[A] INDUSTRY PROFILE

1.1 Insurance

Insurance is basically a sharing device. The losses to assist

resulting from natural calamities like fire, flood, earthquake, accidents,

etc are met out of the common pool contributed by large number of

persons who are exposed to similar risks. This contribution of many is

used to pay the losses suffered by unfortunate few. However the basic

principle is that loss should occur as a result of natural calamities or

unexpected events which are beyond the human control. Secondly

insured person should not make my gains out of insurance.

1.2 Classification of Insurance

Insurance business can be divided into two broad categories, life

and non-life.

1. Life insurance is concerned with making provision for a

specific event happening to the individual, such as death.

2. Non-life is more commonly concerned with the provision for

specific event, which affects a property, such as fire, flood, theft etc.

1.3 Life Insurance Market

The Life Insurance market in India is an underdeveloped market that

was only tapped by the state owned LIC till the entry of private

insurers. The penetration of life insurance products was 19 percent of

the total 400 million of the insurable population. With the entry of the

private insurers the rules of the game have changed.


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The 12 private insurers in the life insurance market have already

grabbed nearly 9 percent of the market in terms of premium income.

The new business premiums of the 12 private players has tripled to Rs

1000 core in 2002- 03 over last year. Meanwhile, state owned LIC's

new premium business has fallen.

The private insurers also seem to be scoring big in other ways- they

are persuading people to take out bigger policies. For instance, the

average size of a life insurance policy before privatization was around

Rs 50,000. That has risen to about Rs 80,000. But the private insurers

are ahead in this game and the average size of their policies is around

Rs 1.1 lakhs to Rs 1.2 lakhs- way bigger than the industry average.

The state owned companies still dominate segments like endowments

and money back policies. But in the annuity or pension products

business, the private insurers have already wrested over 33 percent of

the market. And in the popular unit-linked insurance schemes they

have a virtual monopoly, with over 90 percent of the customers.4

1.4 Important milestones in the life insurance business inIndia:

1912: The Indian Life Assurance Companies Act enacted as the first

statute to regulate the life insurance business.

1928: The Indian Insurance Companies Act enacted to enable the

government to collect statistical information about both life and non-

life insurance businesses.

1938: Earlier legislation consolidated and amended to by the

Insurance Act with the objective of protecting the interests of the

insuring public.


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1956: 245 Indian and foreign insurers and provident societies taken

over by the central government and nationalized. LIC formed by an Act

of Parliament- LIC Act 1956- with a capital contribution of Rs. 5 core

from the Government of India. (2)

1.5 Present Scenario

The Government of India liberalized the insurance sector in March

2000 with the passage of the Insurance Regulatory and Development

Authority (IRDA) Bill, lifting all entry restrictions for private players and

allowing foreign players to enter the market with some limits on direct

foreign ownership. Under the current guidelines, there is a 26 percent

equity cap for foreign partners in an insurance company. There is a

proposal to increase this limit to 49 percent.

The opening up of the sector is likely to lead to greater spread and

deepening of insurance in India and this may also include restructuring

and revitalizing of the public sector companies. In the private sector 12

life insurance and 8 general insurance companies have been

registered. A host of private Insurance companies operating in both lifeand non-life segments have started selling their insurance policies

since 2001.

1.6 GDP contribution

With largest number of life insurance policies in force in the world,

Insurance happens to be a mega opportunity in India. Its a business

growing at the rate of 15-20 per cent annually and presently is of the

order of Rs 450 billion. Together with banking services, it adds about 7

per cent to the countrys GDP. Gross premium collection is nearly 2 per

cent of GDP and funds available with LIC for investments are 8 per cent

of GDP.


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Yet, nearly 80 per cent of Indian population is without life insurance

cover while health insurance and non-life insurance continues to be

below international standards. And this part of the population is also

subject to weak social security and pension systems with hardly any

old age income security. This itself is an indicator that growth potential

for the insurance sector is immense.

[B] COMPANY PROFILE

1.7History of the HDFC Standard Life

HDFC Standard Life first came together for a possible joint

venture, to enter the Life Insurance market, in January 1995. It was

clear from the outset that both companies shared similar values and

beliefs and a strong relationship quickly formed. In October 1995 the

companies signed a 3 year joint venture agreement.

Around this time Standard Life purchased a 5% stake in HDFC,

further strengthening the relationship.

The next three years were filled with uncertainty, due to changes

in government and ongoing delays in getting the IRDA (Insurance

Regulatory and Development authority) Act passed in parliament.

Despite this both companies remained firmly committed to the

venture.

In October 1998, the joint venture agreement was renewed and

additional resource made available. Around this time Standard Life

purchased 2% of Infrastructure Development Finance Company Ltd.

(IDFC). Standard Life also started to use the services of the HDFC

Treasury department to advise them upon their investments in India.

Towards the end of 1999, the opening of the market looked very

promising and both companies agreed the time was right to move the

operation to the next level. Therefore, in January 2000 an expert team


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from the UK joined a handpicked team from HDFC to form the core

project team, based in Mumbai. Around this time Standard Life

purchased a further 5% stake in HDFC and a 5% stake in HDFC Bank.

1.8 Incorporation of HDFC Standard Life Insurance Company

Limited

The company was incorporated on 14th August 2000 under the

name of HDFC Standard Life Insurance Company Limited.

Their ambition from the beginning was to be the first private

company to re-enter the life insurance market in India. On the 23rd of

October 2000, this ambition was realized when HDFC Standard Life

was the first life company to be granted a certificate of registration.

HDFC are the main shareholders in HDFC Standard Life, with

81.4%, while Standard Life owns 18.6%. Given Standard Life's existing

investment in the HDFC Group, this is the maximum investment

allowed under current regulations.

HDFC and Standard Life have a long and close relationship built

upon shared values and trust. The ambition of HDFC Standard Life is tomirror the success of the parent companies and be the yardstick by

which all other insurance companies in India are measured.

All information and material on this site are provided on an "as

is" basis, and are without guarantees or warranties of any kind,

express or implied. Furthermore, any ideas and/or information

provided or gained from this site would not necessarily reflect the

views of HDFC Standard Life or its directors or employees. You are notpermitted to modify copy, reproduce, upload, post or distribute in any

way any material from this site unless expressly permitted by HDFC

Standard Life.


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The materials and/or information available or obtained

at/through this site is/are not guaranteed or warranted in terms of

completeness, correctness, accuracy, reliability or otherwise

howsoever by HDFC Standard Life or its directors or employees.

The information obtained at/or through this site is not and should

not be construed as an offer for a policy or any other assistance. The

terms and conditions on which the policies are sold by HDFC Standard

Life are subject to changes from

Time to time depending on various factors. While the site may be

updated with changes

Periodically, HDFC does not guarantee that this site reflects the

latest amendments/ information at all times or at any time. The terms

and conditions are also largely dependent on the prevalent IRDA

Regulations. HDFC Standard Life does not guarantee that this site is

complete or accurate in its information content as regards the above.

1.9 Customer service

Claims

We understand that bereavement can be difficult to deal with,

especially when you have to arrange for all the formalities in case of

insurance claims.

At HDFC Standard Life we lend a helping hand by enabling faster

settlement of claims and help the family financially at the time of

distress


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To help you arrange the documents we have drawn up a list of

documents that you may be required to send along with the claims

form. This list is for your reference only and the complete list may vary

for each claim.

Policy Servicing

This section is designed to give you information that you may

require incase you wish to make changes in Personal details or Policy

details in your existing policy. The changes that you can avail of are:

Change in Personal Details

Changes you can avail of are:

Changes in your mailing address

Change of Nominee or Appointee

Change in Policy Benefits

Reduction in term of the policy

Removal of additional benefits (Riders)

Reduction in the level cover/premium of your policy

Change in frequency of premium payment

In case of unit linked policies in addition to the above you

can also avail of the following:

Paying additional premium (Top-up)

Changing your current investment composition (FundSwitch)

Changing your future premium direction (Premium

Redirection)

Increase your regular premium


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1.10ACHEVMENT AND AWARDS

May, 2008

Received PC Quest Best IT Implementation Award 2008

HDFC Standard Life received the PC Quest Best IT

Implementation Award 2008 for Consultant Corner, the applications for

its financial consultants, providing centralized control over a vast

geographical spread for key business units such as inventory, training,

licensing, etc. Read more about the Consultant Corner tool in the

HDFCSLinNews Section.

HDFC Standard Life has won the PC Quest Best ITImplementation Award for two years consequently. Last year, the

company received the award for Wonders, its path-breaking

implementation of an enterprise-wide workflow system

March, 2008

Silver Abby at Goa fest 2008

HDFC Standard Life's radio spot for Pension Plans won a Silver Abby in

the radio writing craft category at the Goa fest 2008 organized by the

Advertising Agencies Association of India (AAAI). The radio commercial

Pata Nahin Chala touched several changes in life in the blink of an

eye through an old mans perspective. The objective was drive

awareness and ask people to invest in a pension plan to live life to the
http://www.hdfcinsurance.com/mediacen/hdfcinnews.aspxhttp://www.hdfcinsurance.com/mediacen/hdfcinnews.aspx


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fullest even after retirement, without compromising on ones self-

respect.

HDFC Standard Life received Laadli Media Award 2007 for its 'Big

car' TV commercial. It showed how a daughter wants to be more

responsible towards her family and asks her dad to upgrade to a bigger

car by offering him the extra money required to buy the car.

HDFC Standard Life received this award for two years

consecutively. In 2006, it won for the 'Papa' TV commercial, which

challenged the stereotype parents saving only for their son's education

or daughter's wedding. The company took a bold step by showing

parents saving for their daughter's education abroad, demonstratingprogressive thinking.

Laadli Media Awards, instituted in 2007, by Population First, an

NGO working on women's rights and social development, is given to

professionals in print and electronic media and ad makers for gender

sensitive news reports, articles, print, TV ads, and films.

March, 2008

Unit Linked Savings Plan Tops Mint Best TV Ads Survey

The Unit Linked Savings Plan advertisement of HDFC Standard

Life, one of the leading private insurance companies in India, has

topped Mints Top Television Advertisement survey conducted, for

February 2008. HDFC Standard Lifes Unit Linked Savings Plan

advertisement was ranked 4th in terms of a combined score of ad

awareness and brand recall and 3rd in terms of ad diagnostic scores

(likeability, enjoyment, believability, and claim). The respondents were

between 18 and 40 years. Mints exclusive report, New voices in a

makeover outlines the survey in detail.


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Mr Deepak M Satwalekar, Managing Director and CEO, HDFC

Standard Life, received the QIMPRO Gold Standard Award 2007 in the

business category at the 18th annual Qimpro Awards function. The

award celebrates excellence in individual performance and highlights

the quality achievements of extraordinary individuals in an era of

global competition and expectations.

January, 2008

Sar Utha Ke Jiyo Among Indias 60 Glorious Advertising

Moments

HDFC Standard Lifes advertising slogan honored as one of 60

Glorious Advertising & Marketing Moments' over the last 60

years in India, by 4Ps Business and Marketing magazine. The

magazine said that HDFC Standard Life is one of the first private

insurers to break the ice using the idea of self respect (Sar UthaKe

Jiyo) instead of 'death' to convey its brand proposition. This was then,

followed by others including ICCI Prudential, thus giving HDFC

Standard Life the credit of bringing up one such glorious advertising

and marketing moment in the last 60 years.


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1.11 Products

Each of us leads a unique life and so has unique needs, HDFCStandard Life offers a range of products and invites you to choose the

one that suits you best

Plan Benefits

1. Savings Plans

Endowment Assurance Plan Life Insurance with Savings

Unit Linked Endowment Plan Life Insurance & Savings with choice

of investment funds

Childrens Plan Financial Security for your child

Unit Linked Young Star Plan Financial security for your child

with choice of investment funds

Money Back Plan Life Insurance with Savings

2. Investment Plans

Single Premium Whole Of Life Plan Investment with Life Insurance

3. Protection Plans

Term Assurance Plan Life Insurance at an affordable price

Loan Cover Term Assurance Plan Life Insurance customized for home

loans


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4. Retirement Plans

Personal Pension Plan Savings for retirement

Unit Linked Pension Plan Retirement Savings with a choice

of investment funds

1.12 MISSION, VISION, VALUE OF COMPANY

HDFC MISSION

We aim to be the top new life insurance company in the market. This

does not just mean being the largest or the most productive company

in the market, rather it is a combination of several things like-

Customer service of the highest order

Value for money for customers

Professionalism in carrying out business

Innovative products to cater to different needs of different

customers

Use of technology to improve service standards

Increasing market share

HDFCs VISION

The most successful and admired life insurance company, which

means that we are the most trusted company, the easiest to deal with,

offer the best value for money, and set the standards in the industry.

HDFCs VALUES

Values that we observe while we work:

Integrity

Innovation

Customer centric


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People Care One for all and all for one

Team work

Joy and Simplicity

1.13 Board Members

Mr. Deepak S Parekh Chair man

Mr. Keki M Mistry-Managing director

Mr. Alexander M Crombie

Ms. Marcia D Campbell

Mr. Keith N Skeoch

Mr. Gautam R Divan

Mr. Ranjan Pant

Mr. Ravi Narain

Mr. Deepak M Satwalekar

Ms. Renu S. Karnad-Executive director


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Ch-2 RESEARCH METHODOLOGY

2.1 Problem statement:

To study the factor which influence the various age group to

buy the insurance policy?2.2 Research Objectives

1. Primary objective:

To identify the factor which influence the various age group to

buy the insurance policy?

2. Secondary objectives:

To measure the satisfaction level of the customer of the HDFC

standard life insurance company in the valsad area.

To study the awareness of the life insurance company in the

valsad area.

2.3 Research Design

During the primary research, I have done pilot testing of people in

valsad area. From that I have prepared the questionnaire and then

done my final survey in valsad.

At the initial stage the research is exploratory because it started with

review of literature which was available on internet as well as in books.

After framing the research statement, the research is now Descriptive


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Design because it describes the present scenario at a particular point

time and consists of a sample of the population of interests. Thus it

provides the overall picture at a given time.

Pre-testing

Before the final survey, 10 people were surveyed first to check the

validity of the questionnaire.

2.4 Defining target population

Sampling Design

In this project Descriptive design is used. This is one shot research

study at a given point of time and consists of a sample of the

population of interest. This gives the overall picture at a given time.

Sampling plan

Sampling plan helps to collect the data more accurately from the

market. Sampling plan is made to make the research more effective

when the time available fir research is limited.

Sample description

The people who are living in valsad and surrounding region.

Sample size

For my project, the sample size taken for the survey purpose is of 160

people from valsad region.


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Time duration: 12th May to 07th July. Two months period was

available for the research and data collection.

Sampling frame:

General people of valsad including shop keepers, businessmen,

farmers, service holders, house wives, etc.

Sampling technique

Instead of probability sampling, here Non-probability Convenience

sampling technique is used because of time constraints.

Execution of sampling process

I have collected the data from the people of valsad region through

personal interview with them.

2.5 Research instrument

Questionnaire was used for the purpose of data collection as the

research instrument.

Questionnaire consists of _

Close ended questions ( Many questions includes use of scale)

Open ended questions

2.6 Data collection

For the preparation of the project both types of data are used. i.e.

Primary Data


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Secondary Data

Primary Data:

Primary data are those data which are collected by the researcher for

the first time for his use. These data are pure and therefore more

reliable. Primary data gives the original picture of the study or situation

for which they are collected.

In my project, the primary data are collected through the use of survey

method. In the survey the respondents were personally interviewed for

data collection.

Secondary Data

Secondary data are those data which are once collected by any other

person in past for his purpose and now being used by the researcher

for his purpose. These data are less reliable compared to primary data

because these data may be obsolete with the passing of time and may

have bias information.

In my project, most of the secondary data are collected from internet.

Some data regarding the company were obtained with the help of he

company guide. Some data related to the topic were collected from the

books related to that topic.

2.7 Limitations of the research

As many of the respondents were not that much familiar with

English, I needed to explain each and every question in Guajarati

or Hindi to them.


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The use of SPSS software is new. It took much time to be

understood and to be applied in the project.

The survey was conducted in valsad only so, it can not cover the

preference of other areas client.

2.7Statistical tests used

In this project report, I have used One Sample T-test, paired sample t-

test and measures of central tendency.

One Sample t-test

The one sample t-test is the statistical test which is used to test the

difference between sample statistic and a hypothesized populationparameter. It is used when the types of data are interval in nature.

Paired sample t-test

The paired sample procedure compares the mean of two variables for

a single group. The procedure computes the difference between the

values of the two variables for each case and test weather the average

differs from zero.

For example in a study of high blood pressure, all patients are measure

again. Thus, each subject has two measures, often call before and after

measure. An alternative design for which this test is use is a match

pairs or case control study, in which each record in the data file

contains the response for the patients and also for his or her matched

control subject. In a blood pressure study, patient and also for his or

her matched control subject.

In a blood pressure study, patients and controls might be matched by

75 year old patient with a 75 year old control group member.


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One sample t-test measure the different between the hypotheses

mean and the calculated mean while paired t-test measure the mean

difference between two parameters.

Measures of central tendency

There are three parameters for the measure of central tendency.

Mean is used when the data are of scale type in nature.

Median is used when the data are of ordinal i.e. interval type innature.

Mode is used when the data are of nominal type in nature.

2.8 How to conduct statistical test

I have used SPSS software for applying statistical tests in my research.


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Ch-3 DATA ANALYSIS & INTERPRETATION

Q.1 Kindly rank from 1 to 7 with respect to which ever

company comes first to last in your mind when you think about

insurance?

Purpose:This question helps in knowing the respondents top of the

mind

Awareness regarding various life insurance companies.

RANK=1 PERCENTLIC 114 71.25%HDFC 24 15%ICICI 6 3.75%AVIVA 1 0.625%MAX 4 2.5%BAJAJ 1 0.625%RELIANCE 10 6.25%TOTAL 160 100


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From the above table, we can say that from 160 respondents 114 have

given 1st rank to LIC. Other insurance companies have got very less

frequency in getting 1st rank. So we can say that LIC is at first position

in peoples mind.


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Q-2.Rank the following investment options from 1 to 6

which you prefer most for investment?

Purpose: the purpose of asking this question is to know that which

investment option is mostly used by the respondents

RANK

PERCEN

T

EQUITY 18 11.25FD 73 45.625MUTUAL

FUND 18 11.25INSURANCE 44 27.5POSTAL 6 3.75BONDS 1 0.625TOTAL 160 100


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Here we can see that two investment options bank fix deposit and

Insurance has got higher frequency i.e. 46%and 27% respectively. So

we can say on the bases of the above data that from all the investment

options, these two options viz. fix deposit and Insurance are mostly

used and preferred by the people.

Q.3 what type of insurance policy you have taken?

Purpose: This question is asked to know that which type of life

insurance plan the people have.

PLAN NUMBER PERSENTAGE

life 5 2

investment plan 17 7

pension plan 37 15


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children 12 5

money back 9 4

endowment 55 23

unit licked 30 12

unit licked

endowment 65 27

others 12 5TOTAL

230

As we can see in the above table as well as chart, about 27% of people

has the unit licked endowment plan. This shows that people are more

interested in the unit linked endowment plan.


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Q.4 put the make in below attributes which you prefer

most while purchasing insurance policy?

Purpose. This question is asked to know which factor according to the

policy holder is most important while they have purchase a life

insurance policy.

Desired level (18-25)

ATTRIBUTES 1 2 3 4 5 MEANRisk cover 10 20 3 1 2.8Tax benefits 0 0 3 22 10 4.2Return 0 0 0 3 32 4.91Flexibility 0 0 7 15 7 3.3Safety 0 0 11 14 10 3.9Death

benefits

0 0 0 14 21 4.6

Value added

service

0 10 20 2 3 2.94

Transparenc

y

0 0 3 11 21 4.5

Fund option 8 12 10 5 0 2.3Policy term 10 15 7 4 0 2.2


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Lock in

period

0 0 12 10 13 4

Withdrawal

option in the

policy

0 0 7 12 15 4.1

Risk cover

One sample t- test

Null hypothesis (Ho): There is no significant different between

calculated mean and hypothesized mean (3).in other words, we

hypothesize that policy holder are neutral about the risk cover factor.

i.e. H0: x==3

Alternative hypothesize (H1): There is significant difference

between calculated mean and hypotheses mean. In other words the

policy holders are not neutral about risk cover.

i.e. x, i.e.H1x3

Significant level: 0.05

One-Sample Statistics

N Mean

Std.

Deviation

Std.

Error

Mean

RISKCOVER 35 2.8000 .63246 .10690

One-Sample Test

Test Value = 3

t df Sig. (2- Mean 95% Confidence


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tailed)

Differen

ce

Interval of the

Difference

RISKCOVER -1.871 34 .070 -.20000 -.4173 .0173

Inference

Here the test is performed at 95%significant level and the t value

comes out as .070 which is greater then0.05, means here null

hypothesis is accepted. It can be said that there is no significance

difference between calculated mean and hypothesis mean.

So we can say that according to policy holder of this age group they

are neutral about risk cover factor.

Tax benefits

One sample t- test



hypothesize that according to policy holders tax benefits are importantfor them.

i.e. H0: x==4


between calculated mean and hypotheses mean. In other words

according to policy holders tax benefits are not important for them.

i.e. x, i.e.H1x4



N Mean Std. Std.


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Deviation

Error

Mean

TAX

BENEFITS35 4.2000 .58410 .09873

One-Sample Test

Test Value = 4

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

TAX

BENEFITS2.026 34 .051 .20000 -.0006 .4006

Inference


comes out as .051 which is greater then 0.05, means here null



So we can say that according to policy holder of this age group tax

benefit factor is important for them.

Returns

One sample t- test



hypothesize that according to policy holders return is completely

important for them.

i.e. H0: x==5


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between calculated mean and hypotheses mean. In other according to

policy holders return is not completely important for them.

i.e. x, i.e.H1x5



N Mean

Std.

Deviation

Std.

Error

Mean

RETURNS 34 4.9118 .28790 .04937

One-Sample Test

Test Value = 5

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

RETURNS -1.787 33 .083 -.08824 -.1887 .0122

InferenceHere the test is performed at 95%significant level and the t value




So we can say that according to policy holder of this age group return

on investment is completely important for them

Flexibility

One sample t- test


36/128



hypothesize that according to policy holders flexibility is neutral for

them.

i.e. H0: x==3



policy holders are not neutral about flexibility.

i.e. x, i.e.H1x3



N Mean

Std.

Deviation

Std.

Error

Mean

FLEXIBILITY 35 3.3143 1.65869 .28037

One-Sample Test

Test Value = 3

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

FLEXIBILITY 1.121 34 .270 .31429 -.2555 .8841

Inference






37/128

So we can say that according to policy holder of this age group

flexibility factor is neutral for them.

Safety

One sample t- test



hypothesize that according to policy holders safety is important for

them.

i.e. H0: x==4



according to policy holders safety is not important for them.

i.e. x, i.e.H1x4



N Mean

Std.

Deviation

Std.

Error

Mean

SAFTY 35 3.9714 .78537 .13275

One-Sample Test

Test Value = 4



38/128

tailed)

Differen

ce

Interval of the

Difference

SAFTY -.215 34 .831 -.02857 -.2984 .2412

Inference




difference between calculated mean and hypothesis mean.So we can say that according to policy holder of this age group safety

factor is important for them.

Death benefits

One sample t- test

Null hypothesis (Ho): There is no significant different betweencalculated mean and hypothesized mean (5).in other words, we

hypothesize that according to policy holders death benefit is

completely important for them.

i.e. H0: x==5



according to policy holders death benefits are not completely

important for them.

i.e. x, i.e.H1x5



39/128


N Mean

Std.

Deviation

Std.

Error

Mean

DEATH

BENEFITS35 4.6000 .49705 .08402

One-Sample Test

Test Value = 5

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

DifferenceDEATH

BENEFITS-4.761 34 .000 -.40000 -.5707 -.2293

Inference


comes out as .000 which is less then0.05, means here null hypothesis

is rejected. It can be said that there is significance difference between

calculated mean and hypothesis mean.

Value added service

One sample t- test



hypothesize that policy holder are neutral about the value added

service factor.

i.e. H0: x==3



policy holders are not neutral about value added service.


40/128

i.e. x, i.e.H1x3



N Mean

Std.

Deviation

Std.

Error

Mean

VALUEADDEDSE

RVICE34 2.941 .77621 .13312

One-Sample Test

Test Value = 3

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

VALUEADDEDSE

RVICE

-.442 33 .661 -.05882 -.3297 .2120

Inference





So we can say that according to policy holder of this age group value

added service is neutral for them.

Transparency

One sample t- test


41/128



hypothesize that according to policy holders transparency is important

for them.

i.e. H0: x==4



according to policy holders transparency is not important for them.

i.e. x, i.e.H1x4



N Mean

Std.

Deviation

Std.

Error

Mean

TRANSPARENCY 35 4.5143 .65849 .11131

One-Sample Test

Test Value = 5

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

TRANSPARENCY-4.364

3

4.000 -.48571 -.7119 -.2595

InferenceHere the test is performed at 95%significant level and the t value



calculated mean and hypothesis.


42/128

Fund option

One sample t- test



hypothesize that according to policy holders fund options are not

important for them.

i.e. H0: x==2



according to policy holders fund options are important for them.

i.e. x, i.e.H1x2



N Mean

Std.

Deviation

Std.

Error

Mean

FUNDOPTION 35 2.3429 .99832 .16875

One-Sample Test

Test Value = 2

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference


43/128

FUND OPTION 2.032 34 .050 .34286 -.0001 .6858

Inference


comes out as .050 which is equal to 0.05, means here null hypothesis

is accepted. It can be said that there is no significance difference

between calculated mean and hypothesis mean.

So we can say that according to policy holder of this age group fund

option is not important for them.

Policy term

One sample t- test



hypothesize that according to policy holders policy term is not

important for them.

i.e. H0: x==2



according to policy holders policy term is important for them.

i.e. x, i.e.H1x2



N Mean

Std.

Deviation

Std.

Error

Mean

POLICY TERM 35 2.0857 .91944 .15541


44/128

One-Sample Test

Test Value = 2

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

POLICY TERM .552 34 .585 .08571 -.2301 .4016

Inference





So we can say that according to policy holder of this age group policyterm is not important for them.

Lock in period

One sample t- test



hypothesize that according to policy holders lock in period is important

for them.

i.e. H0: x==4



according to policy holders lock in period is not important for them.

i.e. x, i.e.H1x4



N Mean Std. Std.


45/128

Deviation

Error

Mean

LOCK IN

PERIOD35 4.0286 .85700 .14486

One-Sample Test

Test Value = 4

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

LOCKINPERI

OD.197 34 .845 .02857 -.2658 .3230

Inference





So we can say that according to policy holder of this age group lock in

period is important for them.

Withdrawal option in the policy

One sample t- test



hypothesize that according to policy holders withdrawal option in thepolicy is important for them.

i.e. H0: x==4




46/128

according to policy holders withdrawal option in the policy is not

important for them.

i.e. x, i.e.H1x4



N Mean

Std.

Deviation

Std.

Error

Mean

WITHROWALOPTION IN

THE POLICY

35 4.1143 1.05081 .17762

One-Sample Test

Test Value = 4

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

WITHROWAL

OPTION IN

THE POLICY

.643 34 .524 .11429 -.2467 .4753

Inference




47/128




withdrawal option in the policy is important for them.

The respondents in this age group of 18-25 are looking for more

returns rather then risk cover and value added service.

Death benefits, withdrawal option in the policy are almost important.

While policy term and fund option are least important.



48/128

ATTRIBUTES 1 2 3 4 5 MEAN

Risk cover 0 0 0 25 20 4.44

Tax benefits 0 0 0 3 42 4.93

Return 0 0 2 16 27 4.55

Flexibility 0 0 5 18 23 4.48

Safety 0 0 0 14 31 4.69

Death

benefits

0 0 0 24 21 4.46

Value added

service

0 0 4 20 21 4.37

Transparenc

y

0 0 1 19 25 4.53

Fund option 14 11 12 7 3.2

Policy term 11 7 14 10 3 2.7

Lock in

period

0 0 20 14 11 3.91

Withdrawal

option in the

policy

0 0 8 20 17 4.2

Risk cover

One sample t- test


49/128



hypothesize that according to policy holders withdrawal option in the

policy is important for them.

i.e. H0: x==4




important for them.

i.e. x, i.e.H1x4



N Mean

Std.

Deviatio

n

Std.

Error

Mean

RISKCOVER 45 4.4444 .50252 .07491

One-Sample Test

Test Value = 4

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

RISKCOVER 5.933 44 .000 .44444 .2935 .5954

Inference


comes out as .00 which is less then0.05, means here null hypothesis is


50/128

rejected. It can be said that there is significance difference between


Tax benefits

One sample t- test



hypothesize that according to policy holders tax benefits in the policy

is completely important for them.

i.e. H0: x==5



according to policy holders tax benefits in the policy is not completely

important for them.

i.e. x, i.e.H1x5



N Mean

Std.

Deviatio

n

Std.

Error

Mean

TAXBENEFITS 45 4.93 .25226 .0376

One-Sample Test

Test Value = 5

t df Sig. (2-

tailed)

Mean

Differen

95% Confidence

Interval of the


51/128

ce Difference

TAXBENEFITS 1.7 44 .083 .06667 .1425 .0091

Inference





So we can say that according to policy holder of this age group tax

benefit is completely important for them.

Returns

One sample t- test



hypothesize that according to policy holders return is completely

important for them.

i.e. H0: x==5


between calculated mean and hypotheses mean. In other according to

policy holders return is not completely important for them.

i.e. x, i.e.H1x5



N Mean

Std.

Deviation

Std.

Error

Mean


52/128

RETURNS 45 4.5556 .58603 .08736

One-Sample Test

Test Value = 5

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

RETURNS -5.087 44 .000 -.44444 -.6205 -.2684

Inference



hypothesis is rejected. It can be said that there is significance


Flexibility

One sample t- test



hypothesize that according to policy holders flexibility is important for

them.

i.e. H0: x==4


between calculated mean and hypotheses mean. In other wordsaccording to policy holders flexibility is not important for them.

i.e. x, i.e.H1x4



53/128


N Mean

Std.

Deviation

Std.

Error

Mean

FLEXIBILITY 45 4.4889 .62603 .09332

One-Sample Test

Test Value = 4

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

DifferenceFLEXIBILITY 5.239 44 .000 .48889 .3008 .6770

Inference





Safety

One sample t- test



hypothesize that according to policy holders safety is completely

important for them.


54/128

i.e. H0: x==5



according to policy holders safety is not completely important for

them.

i.e. x, i.e.H1x5



N Mean

Std.

Deviation

Std.

Error

Mean

SAFTY 45 4.6889 .46818 .06979

One-Sample Test

Test Value = 5

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

SAFTY -4.458 44 .000 -.31111 -.4518 -.1705

Inference





Death benefits


55/128

One sample t- test



hypothesize that according to policy holders death benefit is important

for them.

i.e. H0: x==4



according to policy holders death benefits are not important for them.

i.e. x, i.e.H1x4



N Mean

Std.

Deviation

Std.

Error

Mean

DEATHBENEFITS 45 4.4667 .50452 .07521

One-Sample Test

Test Value = 4

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

DEATHBENEFITS 6.205 44 .000 .46667 .3151 .6182

Inference


56/128




calculated mean and hypothesis mean

Value added service

One sample t- test



hypothesize that according to policy holders value added service is

important for them.

i.e. H0: x==4



according to policy holders value added service is not important for

them.

i.e. x, i.e.H1x4



N Mean

Std.

Deviation

Std.

Error

Mean

VALUE ADDED

SERVICE45 4.3778 .61381 .09150


57/128

One-Sample Test

Test Value = 4

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

VALUE ADDED

SERVICE4.129 44 .000 .37778 .1934 .5622

Inference



is rejected. It can be said that there is significance difference betweencalculated mean and hypothesis mean

Transparency

One sample t- test



hypothesize that according to policy holders transparency is


i.e. H0: x==5



according to policy holders transparency is not completely important

for them.

i.e. x, i.e.H1x5




58/128

N Mean

Std.

Deviation

Std.

Error

Mean

TRANSPARENCY 45 4.5333 .54772 .08165

One-Sample Test

Test Value = 5

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

TRANSPARENCY -5.71 44 .000 -.46667 -.6312 -.3021

Inference




calculated mean and hypothesis mean

Fund option

One sample t- test


calculated mean and hypothesized mean (3).in other words, wehypothesize that according to policy holders fund options is neutral for

them.

i.e. H0: x==3


59/128



according to policy holders fund options is not neutral for them.

i.e. x, i.e.H1x3



N Mean

Std.

Deviation

Std.

Error

Mean

FUNDOPTION 45 3.2444 .85694 .12774

One-Sample Test

Test Value = 3

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

FUNDOPTION 1.914 44 .062 .24444 -.0130 .5019

Inference





So we can say that according to policy holder of this age group fund

option is neutral for them.


60/128

Policy term

One sample t- test



hypothesize that according to policy holders policy term is neutral for

them.

i.e. H0: x==3



according to policy holders policy term is not neutral for them.

i.e. x, i.e.H1x3



N Mean

Std.

Deviation

Std.

Error

Mean

POLICYTERM 45 2.7111 1.03621 .15447

One-Sample Test

Test Value = 3

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

POLICYTERM -1.870 44 .068 -.28889 -.6002 .0224

Inference




61/128



So we can say that according to policy holder of this age group policy

term is neutral for them.

Lock in period

One sample t- test




for them.

i.e. H0: x==4




i.e. x, i.e.H1x4



N Mean

Std.

Deviation

Std.

Error

Mean

LOCK IN

PERIOD 45 3.8000 1.28982 .19228

One-Sample Test

Test Value = 4



62/128

tailed)

Differen

ce

Interval of the

Difference

LOCK IN

PERIOD-1.04 44 .304 -.20000 -.5875 .1875

Inference





So we can say that according to policy holder of this age group lock in



One sample t- test





i.e. H0: x==4




important for them.


63/128

i.e. x, i.e.H1x4



N Mean

Std.

Deviation

Std.

Error

Mean

WITHROWAL

OPTION IN

THE POLICY

45 4.2000 .72614 .10825

One-Sample Test

Test Value = 4

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

WITHROWAL

OPTION IN

THE POLICY

1.848 44 .071 .20000 -.0182 .4182

Inference






withdrawal option in the policy is important for them.

According to the respondent of this age group 26-35 tax benefit is the

most important for them. So we can say that the respondent of this


64/128

age group consider insurance as a tax saving instrument rather than

looking for returns than other attributes.

They also feel that the lock in period and the withdrawal option in the

policy are also important.


ATTRIBUTES 1 2 3 4 5 Weighte

d

average

Risk cover 0 0 0 3 42 4.93

Tax benefits 0 0 9 15 21 4.3

Return 0 0 12 15 18 4.1

Flexibility 0 0 4 21 20 4.3

Safety 0 0 8 22 15 4.15


65/128

Death

benefits

0 0 0 14 31 4.68

Value added

service

0 0 17 17 11 3.86

Transparenc

y

0 0 0 2 43 4.84

Fund option 0 0 3 20 22 4.42

Policy term 3 9 10 12 11 3.35

Lock in

period

0 0 12 15 18 4.13

Withdrawal

option in the

policy

0 0 11 17 17 4.13

Risk cover

One sample t- test



hypothesize that according to policy holders risk cover is completely

important for them.

i.e. H0: x==5




66/128

according to policy holders risk cover is not completely important for

them.

i.e. x, i.e.H1x5



N Mean

Std.

Deviation

Std.

Error

Mean

RISKCOVER 45 4.93 .25226 .03761

One-Sample Test

Test Value = 5

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

RISKCOVER 1.773 44 .083 .06667 .1425 .0091Inference


comes out as.083 which is greater then0.05, means here null



So we can say that according to policy holder of this age group risk

cover is completely important for them.

Tax benefits

One sample t- test


67/128


68/128

One sample t- test



hypothesize that according to policy holders return is important for

them.

i.e. H0: x==4



according to policy holders return is not important for them.

i.e. x, i.e.H1x4



N Mean

Std.

Deviation

Std.Error

Mean

RETURNS 45 4.1333 .81464 .12144

One-Sample Test

Test Value = 4

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

RETURNS 1.09 44 .278 .13333 -.1114 .3781

Inference




69/128



So we can say that according to policy holder of this age group return

on investment is important for them.

Flexibility

One sample t- test




them.

i.e. H0: x==4



according to policy holders flexibility is not important for them.

i.e. x, i.e.H1x4



N Mean

Std.

Deviation

Std.

Error

Mean

FLEXIBILITY 45 4.3556 .64511 .09617

One-Sample Test

Test Value = 4



70/128

tailed)

Differen

ce

Interval of the

Difference

FLEXIBILITY 3.6

944 .001 .35556 .1617 .5494

Inference


comes out as .001 which is less then 0.05, means here null hypothesis



Safety

One sample t- test



hypothesize that according to policy holders safety is important for

them.

i.e. H0: x==4

Alternative hypothesize (H1): There is significant differencebetween calculated mean and hypotheses mean. In other words

according to policy holders safety is not important for them.

i.e. x, i.e.H1x4



N Mean

Std.

Deviation

Std.

Error

Mean

SAFTY 45 4.155 .70568 .10520

One-Sample Test


71/128

Test Value = 4

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

SAFTY 1.479 44 .146 .15556 .0565 .3676

Inference





So we can say that according to policy holder of this age group safety

is important for them.

Death benefits

One sample t- test



hypothesize that according to policy holders death benefits is


i.e. H0: x==5


between calculated mean and hypotheses mean. In other wordsaccording to policy holders death benefits is not completely important

for them.

i.e. x, i.e.H1x5



72/128


N Mean

Std.

Deviation

Std.

Error

Mean

DEATH

BENEFITS45 4.6889 .46818 .06979

One-Sample Test

Test Value = 5

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

DifferenceDEATH

BENEFITS-4.458 44 .000 -.31111 -.4518 -.1705

Inference





Value added service

One sample t- test



hypothesize that according to policy holders value added service is

important for them.

i.e. H0: x==4


73/128



according to policy holders value added service is not important for

them.

i.e. x, i.e.H1x4



N Mean

Std.

Deviation

Std.

Error

Mean

VALUE ADDED

SERVICE45 3.8667 .78625 .11721

One-Sample Test

Test Value = 4

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

VALUE ADDED

SERVICE-1.138 44 .261 -.13333 -.3695 .1029

Inference



hypothesis is accepted. It can be said that there is no significancedifference between calculated mean and hypothesis mean.

So we can say that according to policy holder of this age group value

added service is important for them.


74/128

Transparency

One sample t- test



hypothesize that according to policy holders transparency is


i.e. H0: x==5



according to policy holders transparency is not completely important

for them.

i.e. x, i.e.H1x5



N Mean

Std.

Deviation

Std.

Error

Mean

TRANSPARENCY 45 4.9556 .20841 .03107

One-Sample Test

Test Value = 5

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

TRANSPARENCY -1.431 44 .160 -.04444 -.1071 .0182


75/128

Inference






transparency is completely important for them.

Fund option

One sample t- test



hypothesize that according to policy holders fund options is important

for them.

i.e. H0: x==4


between calculated mean and hypotheses mean. In other wordsaccording to policy holders fund options is not important for them.

i.e. x, i.e.H1x4



N Mean

Std.

Deviation

Std.

Error

Mean

FUND

OPTION45 4.4222 .62118 .09260

One-Sample Test


76/128

Test Value = 4

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

FUND

OPTION4.560 44 .000 .42222 .2356 .6088

Inference





Policy term

One sample t- test



hypothesize that according to policy holders policy term is neutral for

them.

i.e. H0: x==3



according to policy holders policy term is not neutral for them.

i.e. x, i.e.H1x3



N Mean Std. Std.


77/128

Deviation

Error

Mean

POLICY

TERM45 3.3556 1.24600 .18574

One-Sample Test

Test Value = 3

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

POLICY TERM 1.91 44 .062 .35556 .0188 .7299

Inference





So we can say that the policy holder of this age group is neutral about

policy term factor.

Lock in period

One sample t- test




for them.

i.e. H0: x==4


78/128




i.e. x, i.e.H1x4


N Mean

Std.

Deviation

Std.

Error

Mean

LOCK IN

PERIOD45 4.1333 .81464 .12144

One-Sample Test

Test Value = 4

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

LOCK IN

PERIOD 1.098 44 .278 .13333 -.1114 .3781

Inference




difference between calculated mean and hypothesis mean.So we can say that according to policy holder of this age group lock in




79/128

One sample t- test





i.e. H0: x==4




important for them.

i.e. x, i.e.H1x4



N Mean

Std.

Deviation

Std.

Error

Mean

WITHROWAL

OPTION IN

THE POLICY

45 4.1333 .78625 .11721

One-Sample Test

Test Value = 4

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

WITHROWAL

OPTION IN

THE POLICY

1.138 44 .261 .13333 -.1029 .3695

Inference


80/128






withrowal option in the policy is important for them.

According to responded of this age group (36-45)Risk cover and transparency is completely important for them. so we

can say the respondent of this age group primary looking for risk cover

and transparency. While return, safety, value added service, lock in

period, withdrawal option in the policy are important for them.


81/128

Desired level (46&above)

ATTRIBUTES 1 2 3 4 5 Weighted

average

Risk cover 0 0 7 6 22 4.42

Tax benefits 0 0 0 12 23 4.65

Return 0 0 8 14 13 4.14

Flexibility 0 4 7 12 12 3.91

Safety 0 0 0 15 20 4.57

Death

benefits

0 0 0 2 33 4.94

Value added

service

0 1 4 16 14 4.22

Transparenc

y

0 0 3 12 20 4.48

Fund option 0 0 3 15 17 4.4

Policy term 0 0 8 12 15 4.2


82/128

Lock in

period

0 0 0 13 22 4.62

Withdrawal

option in the

policy

0 0 0 2 33 4.94

Risk cover

One sample t- test





i.e. H0: x==4




important for them.

i.e. x, i.e.H1x4



N Mean Std.

Deviation

Std.

Error


83/128


84/128

i.e. x, i.e.H1x5



N Mean

Std.

Deviation

Std.

Error

Mean

TAX

BENEFITS35 4.6571 .48159 .08140

One-Sample Test

Test Value = 5

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

TAX

BENEFITS-4.212 34 .000 -.34286 -.5083 -.1774

Inference


comes out as .000which is less then 0.05, means here null hypothesis



Returns

One sample t- test



hypothesize that according to policy holders return is important for

them.


85/128


86/128

Flexibility

One sample t- test




them.

i.e. H0: x==4



according to policy holders flexibility is not important for them.

i.e. x, i.e.H1x4



N Mean

Std.

Deviation

Std.

Error

Mean

FLEXIBILITY 35 3.9143 1.01087 .17087

One-Sample Test

Test Value = 4

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

FLEXIBILITY -.502 34 .619 -.08571 -.4330 .2615

Inference


87/128






flexibility is important for them.

Safety

One sample t- test


calculated mean and hypothesized mean (5).in other words, wehypothesize that according to policy holders safety is completely

important for them.

i.e. H0: x==5



according to policy holders safety is not completely important for

them.

i.e. x, i.e.H1x5



N Mean

Std.

Deviation

Std.

Error

Mean

SAFTY 35 4.5714 .50210 .08487

One-Sample Test


88/128

Test Value = 5

t df

Sig. (2-

tailed)

Mean

Differen

ce

95% Confidence

Interval of the

Difference

SAFTY -5.050 34 .000 -.42857 -.6010 -.2561

Inference





Death benefi

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Jignesh Final Report

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