This document discusses sampling and sampling design. It defines key terms like population, sample, census. It notes the features, limitations and types of sampling including probability and non-probability sampling methods. It also covers determining sample size, sampling distribution, attitudes measurement and different types of scales used to measure attitudes like nominal, ordinal, ratio and interval scales. Criteria for a good scale include validity and reliability. Different types of validity like content, construct, predictive and concurrent validity are also discussed.

1. 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 large
Population of size small
large

2. 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.

3. 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.

4. Types of sampling-
1.Probability sampling methods
2.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.

5. 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.

6. d.Cluster sampling-
Define particular area.
Select random sampling technique called area
sampling.
Exp- Delhi
East Delhi
West Delhi
South Delhi
Central Delhi
Cluster sampling
East Delhi
Central Delhi

7. 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

8. 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.

9. 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.

10. 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

11. 1.Define the population-
Survey on the consumption of tea in Gujarat.
a. Elements- tea
b.Sample unit- house holds, house wife.
c. Extent – Gujarat state
d.Time – 1-10-2013
Survey of the recently introduced product by a
company- (Delhi and New Delhi),
Elements- company product
Sampling units- retail outlets, supermarket.
Extent – Delhi and New Delhi

12. 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 population
Sample 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.

13. 4.Specify the sample design-
a. Probability b. Non-probability
5.Determine sample size- how many element of the
target population.
6.Select the sample unit-choose/select of the right
sample.

14. 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 errors
a. Sampling error- a sample is an exact
representation of the total population. The
difference b/w the unknown values of population

15. 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

16. 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.

17. 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.

18. 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.

19. 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.

20. 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.

21. 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

22. Sample sample mean
1.A,B 1.5
2.A,C 2
3.A,D 2.5
4.A,E 3
5.A,F 3.5
6.B,C 2.5
7.B,D 3
8.B,E 3.5
9.B,F 4
10.C,D 3.5

23. Sample sample mean
11. C,E 4
12. C,F 4.5
13. D,E 4.5
14. D,F 5
15. E,F 5.5

24. 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

25. ∑fx
N
52.5/15=3.5

26. 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.

27. 3.Behavioural component- emotional, like/ dislike,
good/ bad. (actual purchase behavior).
Link between attitudes and behavior-
Attitudes-purchase Mercedes
Behavior-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.

28. 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 science
Length, weight. Happiness, creativity
(easy ) (very difficult)

29. 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 scales
a.Likert scales
b. Semantic differential
scales.
c.Thurston scales.

30. 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 satisfied
Very satisfied very dissatisfied
+2 +1 0 -1 -2
2. Comparative scales- “excellent” “very good”
“good” “fair” and “poor”
Comparison of product/ service.

31. Exp- comparison public school with govt. school
Very 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.

32. Company image
Functions
Price
Comfort
Design
Attributes
rating
1
2
3
4
5
No. Of
respondents
given rating
40
60
40
30
30

33. 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 respondent
Placement 15
Faculty 25
Location 20

34. Computer lab 10
Library 30
100

35. 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 +2
Agree +1
Indifferent 0
Disagree -1
Strongly disagree -2

36. 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 +4
A is the most favorably disposed (eliminate) towards
news paper advertisement.

37. 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

38. Semantic differential scales-
Important
unimportant
Strong weak

39. 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-

40. 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-

41. Statement
1 2.6
2 7.0
3 4.0
4 1.80
5 3.0
Suppose 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.

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

43. Types of scales-
1.Nominal scales
2. Ordinal scales
3. Ratio scales
4. Interval scales
1. 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.

44. 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

45. House hold income
E 110,000
House hold order of house hold on
the basis of annual income
A C
B D
C E
D B
E A

46. 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.

47. 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-

48. 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.

49. 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

50. 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.

51. 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.

52. 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”.

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