Unit -2 Sample and sampling design-A sub group of the elements of the population

selected for the participation in the study. Census-a complete enumeration of the elements of

a population or study object. sample census budget small largePopulation of size small largeTime available short long

Feature of sampling-1.Econommy-less expensive and less time

consuming.2.Reliability- conclusion of sample survey is almost

reliable.3.Detailed study- define about the multiple

population.4.Scientific base- we are focusing a particular

object.

Limitation of sampling-1.Less accuracy- in this case if researcher select

biased data then sampling will be less accuracy.2.Misleading conclusion- biased data create

misleading conclusion.3.Need for specialised knowledge- sampling

required specific knowledge.

Types of sampling-1.Probability sampling methods2.Non-probability sampling methods

1.Probability sampling- in this case result will known.

Types of probability sampling-a. Sample random sampling-Selection of items for a sample depends upon

chance.Equal probability to all population units.Exp-lottery methods is the process of simple

random sampling.

b.Stratified random sampling-Population is divided in to several groups.Proper representation to all the distinct

characters.Exp- selection of boys and girls in class room. c.systematic random sampling-Complete list of the population.Select one specified name.Exp- selection of student depend upon marks,

attendance, etc.

d.Cluster sampling-Define particular area.Select random sampling technique called area

sampling.

Exp- Delhi

East Delhi

West Delhi

South Delhi

Central Delhi

Cluster samplingEast DelhiCentral Delhi

e.Multi-stage sampling- in this case one population going through different way.

Exp-population large group smaller group final group.

State distt. Mandal village

Non-probability sampling techniques-1.Deliberate or purposive sampling- true representative This type of sampling mostly in social science

research.Helps in making case studies. 2.Quota sampling- Collect information from an assigned number.Select respondents with in the quota

according to their judgment.It is very popular in opinion surveys and

market studies.

3.Convenience sampling-Sampling do in nearest place.Readily available list such as telephone

directories.Important in exploratory research.4.Judgement sampling-When selection of a few units, based on

judgment.

Sampling process/ steps in sampling design-

Define the population

Identify sample frame

Specify the sampling unit

Specify the sample design

Determine sample size

Select the sample unit

Collected the data from the designated sample

1.Define the population-Survey on the consumption of tea in Gujarat. a. Elements- teab. Sample unit- house holds, house wife.c. Extent – Gujarat stated. Time – 1-10-2013Survey of the recently introduced product by a

company- (Delhi and New Delhi), Elements- company productSampling units- retail outlets, supermarket.Extent – Delhi and New Delhi

2.Identify the sampling frame- define list according block list and localities of a city, a map.

3.Specify the sampling- Sampling unit-element of the target populationSample of house wife/house hold,-directly access

(contact)Select –house holds as the sampling units.Then take interview each selected house olds.Time-office time/normal time, whatever you

choose.

4.Specify the sample design-a. Probability b. Non-probability5.Determine sample size- how many element of the

target population.6.Select the sample unit-choose/select of the right

sample.

Problems in sampling-Some time sampling creates some problem

because it would not be applicable in every situation like- NDPL can not take a reading of sampled number of households meters for computing electricity bills to the whole population of its customers.

Types of sampling problems-a. Sampling error.b. Data collection errorsa. Sampling error- a sample is an exact

representation of the total population. The difference b/w the unknown values of population

And the values obtained from the sample are sampling errors.

Exp-sample of 400 students, we find out that 30% students are earned expense themselves.

But when interview conduct each and every unit of the population then 40% of the total expense are earned by themselves.

(40-30)=10 sampling error

Data collection errors-a.Non-response errors- when respondents who

refuse to respond or difficult to approach. These respondents who do not participate in a survey may be affect the result of the study.

b.Selection errors- sometimes the procedures adopted for the selection of units of population are improper. these may be wrongly selected sampling frame.

c.Measurent errors-these errors may be also be due to the wrong recording of data by the interviewer. Such errors may also affects result due to wrong editing, coding, or interpretation of data.

d.Predicition errors- certain errors enter in the study due to the estimated or substitute data used to predict certain activities. All these errors can be rectified by proper training to the investigators.

Determine the sample size-Size of sample- if the sample is either too small or

too big, it shall make the study difficult.“An optimum sample in survey is done, which

fulfills the requirements of efficiency, representativeness, reliability and flexibility . The sample should be small enough to avoid unnecessary expenses and large enough to avoid intolerable sampling error”

Factors to be considered in sample size-1.The size of the universe- the bigger should be the

sample size.

2.The resource available- if the resource available are vast, then the large sample size could be taken.

3. The degree of accuracy- degree of accuracy desired the larger should be the sample size. It is not necessary that bigger samples always ensure greater accuracy.

4. Homogeneity or heterogeneity of the universe- if the universe consist of homogeneous units. A small sample may serve the purpose, but if the universe consist of heterogeneous units the a large sample may be required.

5. Nature of study- for a continuous study, a small sample may be suitable. But for studies which are not likely to be repeated. It may be necessary to take a large number of sample size.

6. Methods of sampling- if the size is random it may necessitate a bigger sample size. If stratified sampling plan, a small sample may give better results.

Sampling distribution of mean-Identity of person amount (X) X2

A 1 1 B 2 4 C 3 9 D 4 16 E 5 25 F 6 36 21

Sample sample mean1. A,B 1.52. A,C 23. A,D 2.54. A,E 35. A,F 3.56. B,C 2.57. B,D 38. B,E 3.59. B,F 410.C,D 3.5

Sample sample mean11. C,E 412. C,F 4.513. D,E 4.514. D,F 515. E,F 5.5

Sample mean X frequency F FX 1.5 1 1.5 2.0 1 2.0 2.5 2 5.0 3.0 2 6.0

3.5 3 10.5 4.0 2 8.0 4.5 2 9.0 5.0 1 5.0 5.5 1 5.5 ∑N=15 ∑ FX=52.5

∑fxN52.5/15=3.5

Attitude-Perception of consumers towards products.Perception regarding particular product, how

company will be capable to change consumer attitudes.

Components of attitudes-1.Cognitive component- faith, strength, economy. (advertising, pricing,) a cognitive component

indicates that the respondent is aware of and knows about a given object.

2.An affective component- price, quality, brand, I like this product. For X product advertising is not

good.

3.Behavioural component- emotional, like/ dislike, good/ bad. (actual purchase behavior).

Link between attitudes and behavior-Attitudes-purchase MercedesBehavior-purchase a less desirable TATA Indica

( economy constraints)Attitudes- it is the perception/ observation of any

consumers towards products/ services.Behavior- it is the practical implementation due to

attitudes/ economy concern.

Attitudes measurement process-Segmentation of marketing according product/

consumer, area, territory, age, height, weight, etc. Difficulty of attitude measurement-“physical science of attitude measurement is easy

rather than social science”

Physical science social scienceLength, weight. Happiness, creativity(easy ) (very difficult)

Attitude measurement scaling technique in M.R-

Single item scale

a.Itemised category scale.b.Comparative scales.c. Rank order scales.d. Q-sort scales.e.Constant sum scales.

Multi-item scalesa.Likert scalesb. Semantic differential scales.c.Thurston scales.

Single item scale-Single item scales are those that have only one item

to measure a conduct.1.Itemised category scales- in this case we observe-

very satisfied, some what satisfied quite satisfied, not at all satisfiedVery satisfied very dissatisfied+2 +1 0 -1 -22. Comparative scales- “excellent” “very good”

“good” “fair” and “poor”Comparison of product/ service.

Exp- comparison public school with govt. schoolVery superior neither superior very inferior nor inferior

3. Rank order scales-in this case we use number, letters, or other symbols used to rank items. Rank given by consumer’s for every company-

Exp- sample of 100 washing machine owner (customers) of different brands.

Company imageFunctionsPriceComfortDesign

Attributes rating

12345

No. Of respondents given rating

4060403030

4. Q- sort scaling- when the respondent will be high through the above methods then follow the Q-sort scaling. Respondents are asked to sort the various features or objects that are categorised in to various groups.

5. Constant sum scales- providing fixed no. of response.Exp- divide 100 response among the following

characteristic.Rating points respondentPlacement 15 Faculty 25Location 20

Computer lab 10Library 30 100

Multi-item scales-1.Likert scales-a. item would be evaluated on the basis of how will it?b. Discriminated b/w those person whose total score is high and those whose score

is low.c. It is represent favorable/ unfavorable attitudes towards given object.Exp- Likert scale use in 5 categories-Strongly agree +2Agree +1Indifferent 0

Disagree -1 Strongly disagree -2

Exp-Is news paper advertisement affect the quality paper?

interviewee statements A B C 1 +2 -1 +1 2 0 -2 0 3 +2 0 -1 4 +2 -1 +2 5 +1 -2 +2 total +7 -6 +4A is the most favorably disposed (eliminate)

towards news paper advertisement.

B is the least disposed C is the moderate disposed.

2.Semantic /Semantic differential scale- in this case use of extensive words rather than no. respondents describes their feelings about the products or brands on scales with semantic levels.

Exp- semantic and semantic differential scales- semantic scales-

good

Extremely slightly slightly extremely

Quite neither quite bad

Semantic differential scales-

Important unimportant

Strong weak

3.Thurstone –differential scales-people could not assign quantitative measurement

to their attitude, they could tell differences between attitudes represented by two different statement and could identify item those are half-way between the two-

Exp- we have taken (100-200) sample/statement relating to attitude measurement, with the help of 20 judges. They sorted in to 5 positions.

This scaling was used to measure consumers attitude towards news papers advertisement-

Statements range-1.Newspaper ads are monotonous.2. Most of the news paper ads are pretty bad.3. News paper ads do not interfere too much with

reading of news.4. I have no opinion for or against the nes paper

ads.5. I like news paper ads at times. In this survey each of the above statements was

assigned a value based on its original ratings by the judges-

Statement 1 2.6 2 7.0 3 4.0 4 1.80 5 3.0Suppose interviewee A chose/ select statement

1,4,5 with he/ she agrees, then average score would be – 2.6+1.8+3.0 or 7.4/3= 2.47

If interviewee B select statements 1,2,3, & 5,then the higher average score would be – 2.6+7.0+4+3.0 or 4.15.

Interviewee A would be ranked higher (lower the number, the more positive attitude) than B.

Types of scales-1.Nominal scales2. Ordinal scales3. Ratio scales4. Interval scales1. Nominal scales- classification of individuals,

companies, products, brands, or other entities in to categories where no order is implied. Assigning number to hockey team players. Assigned no. In this case, serve to identify players position in the team. In some cases, the assigned no. can provide insight in to some aspect of the time, position, or location.

Exp-pincodes not only identify territories but can also be used to determine geographical location,

Permissible statistics-mean, chi-square test.2. Ordinal scales- it is indicate the order, this is

possible when one is able to distinguish elements on the basis of single direction-

House hold income A 6000 B 10,000 C 480,000 D 120,000

House hold income E 110,000House hold order of house hold on the basis of annual incomeA CB DC ED BE A

3.Ratio scales- it is commonly used physical dimension, such as height, weight, distance, money value and population count.

Exp- 9 and 45 are in the ratio 1:5,Marketing phenomena- sales (unit/rupeese)

4.Interval scales- measurent of the temperature, temperature 100 degrees. 20 degrees is warmer than 80 degrees and 20 degrees cooler than 120 degrees.

In summer season the attitude would be differ regarding cooler and ac for particular place.

Criteria for a good scale-1.Validity- “a measuring instrument is valid when it

measure what it is supposed to measure. The instrument is valid to the extent that its measurements are free from systematic error”

2.Relability- it may be defined as a measurement instrument is reliable when the results are consistent. The measurement is reliable to the extent that its measurement are free from non systematic random error.

Validity –1. Content validity- the researcher should first define

the problem clearly. Identify the items to be-

measured and a suitable scale for the purpose.Content validity will depend on the judgment of the

researcher and this is likely to vary from individual to individual.

Exp- knowledge and skill should be vary from individual to individual profession.

Exp- computer literacy includes skills in operating – system, word processing, data base, graphics, internet, and many others.

“if the researcher want to know the knowledge about the computer skills, then they asked the above question from the population of computer skills, content should be related to the topic.

2.Construct validity- it can be measured only indirectly on the basis of answers given by the respondent. In a situations of this type, the test of construct validity is used.

Exp- the status of an individual in a society may be depend upon such variables as the level of- education, occupations or ownership of a cars and house.

3.Predict validity- first measure the attitude then predict the future behavior on the basis of this measurement.

It is signifies how best the researcher can guess the future performance, from his knowledge of the attitude score.

Exp- questionnaire (correctly) for the demand forecasting for a product is predict validity.

4.Concurrent validity- an attitude scale on one variable can be used to estimate score on another variable.

Exp- one may decide the social status of the respondent on the basis of their attitude towards savings.

Reliability-1.Test –re-test reliability- this form of reliability

involves repeated measurement of the same respondent or group using the same scaling technique under similar condition.

When the correlation is low then the reliability is too less.

Exp- suppose a person takes his weight on a weighting machine which gives accurate results, then the scale is both reliable and valid. When the machine always records 2kg. More than his actual weight then the scale is reliable but not valid.

2.alternate- forms reliability- two different forms of test based on the same content. On one occasion to the same examinations, like different types of entrance exam. For MBA.

3.spilt-half reliability- In case of computer knowledge one statements.

a)I feel very negative about computer in general.b)I enjoy using computer.“people who strongly agree in statement 1, should

be strongly disagree in 2nd statement . If the rating of both statements is high or low among several respondents. Then the response are said to be inconsistent and pattern less”.

Exp- when no pattern is found in the students response, probability the test is too difficult and students just guess the answer randomly.