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Sampling
Process of Sampling
          Clearly define target population
          Select sampling frame
         Choose sampling technique
         Determine sampling size
         Collect data
        Assess response rate
Sampling Types / Sampling Methods
        Probability Sampling Method ( Random )
                         Simple Random Sampling
                         Stratified Sampling
                        Cluster Sampling
                        Systematic Sampling
        Non-Probability Sampling Method ( Non-Random)
                        Convenience Sampling
                        Judgmental or Purposive Sampling
                        Snowball Sampling
                        Quota Sampling
                                             Accidental Sampling
                                                                                                                                                                       

                                 Sampling                                  

A sample is defined as a smaller set of data that a researcher chooses or selects from a larger population by using a pre-defined selection method. These element are known a sample points, sampling units, or observation. Creating a sample is an efficient method of conducting research. In most cases, it is impossible or costly and time-consuming to research the whole population. Hence, examining the sample provides insights that the researcher can apply to the entire population.





Process of Sampling                                                                             

1. Clearly define target population

2. Select sampling frame

3. Choose sampling technique

4. Determine sampling size

5. Collect data

6. Assess response rate


1. Clearly Define Target Population

The first stage in the sampling process is to clearly difine target population. Population is comenonly related to the number of people living in a particular country.


2. Select Sampling Frame

A Sampling frame is a list of the actual cases from which sample will be drawn. The sampling frame must be representative of the population.


3. Choose Sampling Technique or method

Prior to examining the various types of sampling method, it is worth noting what is meant by sampling, along with reasons why researchers are likely to select a sample.

Taking a subset from chosen sampling frame or entire population is called sampling.

Sampling can be used to make inference about a population or to make generalization in relation to existing theory.


4. Determine Sample Size

In order to generalize from a random sample and avoid sampling errors or biases, a randon sample needs to be of adequate size, what is adequate depends on several issues which often confuse people doing surveys for the first time.

This is because what is important here is not the proportion of the research population that gets sampled, but the absolute size of the sample selected relative to the complexity of the population, the aims of the research and the kinds of statistical manipulation that will be used in data analysis.


5. Collect Data

Once target population, sampling frame, sampling technique and sample size have been established, the next step is to collect data.


6. Assess Response Rate

Response rate is the number of cases agreeing to take part in the study. There cases are taken from original sample. In reality, most researchers never achieve a 100 Percent response rate.

Reasons for this might include refusal to respond, ineligibility to respond, inability to respond, or the respondent has been located but researchers are unables to make content.

In sum, response rate is important because each non response is liable to bias the final sample. 

Clearly defining sample, employing the right sampling technique and generating a large sample, in some respects can help to reduce the likelihood of sample bias.






 Sampling Types / Sampling Methods                                                

                                                               Sampling Methods

A. Probability Sampling Method ( Random )    B. Non-Probability Sampling Method ( Non-Random)

1. Simple Random Sampling                                                          i. Convenience Sampling

2. Stratified Sampling                                                                    ii. Judgmental or Purposive Sampling

3. Cluster Sampling                                                                      iii. Snowball Sampling

4. Systematic Sampling                                                                iv. Quota Sampling


A. Probability Sampling (Equal chance)                                             

Probability sampling to a sampling technique in which sample from a largar population are chosen using a method based on the theory of probability.

This sampling method considers every member of the population and forms samples on the basis of a fixed process.

For example, in a population of 1000 members, each of there members will have 1/100 chances of being selected to be a part of a sample. It gets rid of bias in the population and gives a faire chance to all members to be included in the sample.


1. Sample Random Sampling ( Homogeneous )     

One of the best probability sampling techniques that helps in saving time and resources, is the simple random sampling method.

It is a trustworthy method of obtaining information where every single member of a population is chosen randomly, merely by chance and each individual has the exact. Same probability of being chosen to be a part of a sample.

For example, in an organization of 500 employes. if the HR team decided on conducting team building activities, it is highly likely that they would prefer picking chits out of a bowl. In this case, each of the 500 employes has an equal opportunity of being selected.

Like - Lottery Method





2. Stratified Rondom sampling ( Heterogeneous )

Stratified sampling is where the population is divided into strata (on subgroups) and a random simple is taken from each subgroup.

A subgroup is a natural set of items.

subgroups might be based on company size, gender or occupation (to name but a few). stratified sampling is often used where there is a great deal of variation within a population. Its purpose is to ensure that every stratum is adequately represented.





3. Cluster Sampling ()

Cluster sampling is a method where the researcher divide the entire population into sections or cluster that represent a population.

Clusters are identified and included in a sample on the basis of defining demographic parameters such as age, location, sex etc. Which makes it extremely easy for a survey creator to derive effective inference from the feedback.

Naturally accruing group.



Different with Stratified Rondom sampling Cluster Sampling
















4. Systematic Sampling

Using systematic sampling method, member's of a sample are chosen at regular intervals of a population.

It requires selection of a starting point for the sample and sample size that can be repeated at regular intervals.

This type of sampling method has а predefined interval and hence this sampling technique is the least time consuming.

For example, a researcher intends to collect a systematic sample of 500 people in a population of 5000. Each element of the population will be mumbered from 1-5000 and every 10 th individual will be chosen to be a part of the sample.






 B. Non- Probability Sampling (Not equal chance)                            

Non-Probability sampling is dfined as a sampling technique in which the researcher selects samples based on the subjective judgement of the researcher rather than random selection.

This sampling method depends heavily on the expertise of the researchers. 

It is carried out by observation and researcher use it widely in qualitative researcher.

* higher margin of error, loaded with biases.


a. Convenience Sampling

Convenience sampling is a Non-Probability sampling technique where samples are selected from the population only because they are conveniently available to the researcher.

Researchers choose these samples just because hey are easy to recruit, and the researcher did not consider selecting a sample that represents the entire population.

* Easily accessible of Researcher.


b. Judgement sampling

In the Judgement sampling method, researchers selects the samples based purely on the researcher's knowledge and credibility.

In other words, researchers choose only those people who they deem fit to participate in the research study.

Judgement or purposive sampling is not a scientific method of sampling, and the downside to this sampling technique is that the preconceived notions of a researcher can influence the results.

Thus, this research technique involves a high amount of ambiguity.


c. Quota sampling

Quota sampling is a Non-Probability sampling technique where in the assembled sample has the same proportions of individuals as the entire population with respect to known characteristics, traits or focused phenomenon.

Fixed number of person researcher decided on different category.


d. Snowball Sampling / Chain System

Snowball sampling helps researchers find a sample when they are difficult to locate.

Researchers use this technique when the sample size is small and not easily available.

This sampling system works like the referral program.

Once the researchers find suitable subjects he asks them for assistance to seek similar subjects to from o considerably good size sample.






Accidental Sampling 

It is similar to quota sampling, but it is used in market research ( in market places ). Where a researcher can come across any person and they may not have any information.

* No any pre-structed.



















Notes : 

* The sample size for any research study depends upon four (4p)p

1. Purpose - The required precision of study.

2. Population - The size and nature of population under study.

3. Procedure - The time, budget of the studies.

4. Publishing - The inportance of the study.











Question : 

1. Generalized conclusion on the basis of a sample is technically known as [December 2007] 
a. Data analysis and interpretation                  b. Parameter inference 
c. Statistical inference                                     d. All the above
Ans: 

2. The process of selecting a subset of a population for a survey is known as 
a. Survey research           c. Triangulation 
b. Representation            d. Sampling
Ans: 

3. Researchers ultimately want the answer to a research question to pertain to the 
a. Sample                              b. Accessible population 
c. Target population              d. World
Ans: 

4. When a research problem is related to heterogeneous population, the most suitable method is [December 2008] 
a. Cluster sampling               c. Convenient sampling 
b. Stratified sampling            d. Lottery method
Ans: 

5. An investigator wants to study the vocational aspirations of visually challenged children in a wide geographical area. He should select his sample by using 
a. Simple random sampling                      b. Stratified sampling 
c. Purposive sampling                              d. Convenient sampling
Ans: 

6. The type of sampling where each person in population has equal chance of being selected is 
a. Probability sampling                    b. Non-probability sampling 
c. Judgement sampling                     d. None of the above
Ans: 

7. Here, some people have greater chance of being elected than other members of the population. It is 
a. Probability sampling                    b. Non-probability sampling 
c. Quota sampling                            d. None of the above
Ans: 

8. Which of the following variables cannot be expressed in quantitative terms? [December 2010] 
a. Socio-economic status                     b. Marital status 
c. Numerical aptitude                          d. Professional attitude
Ans: 

9. A representative sample is essential in 
a. Survey method                        c. Case study 
b. Experimental method              d. Clinical method
Ans: 

10. Which one is known as non-probability sampling? 
a. Cluster sampling                         b. Quota sampling 
c. Systematic sampling                   d. Stratified random sampling
Ans: 

11. While the statistical measure based upon entire population is called parameter, the measure based upon a sample is known as 
a. Sample parameter                   c. Statistic 
b. Inference                                 d. None of the above
Ans: 

12. A researcher selects a probability sample of 100 out of the total population. It is called 
a. A quota sample                                 b. A simple random sample 
c. A stratified random sample               d. A systematic sample
Ans: 

13. A researcher divides the school students on the basis of gender and then by using the random digit table, he selects some of them from each group. This process is called 
a. Stratified sampling                               b. Stratified random sampling 
c. Representative sampling                      d. None of the above


14. To ensure accuracy of a research, the sample should be 
a. Taken randomly                                       b. Fixed by quota 
c. Representative of the population             d. Purposive
Ans: 

15. A researcher can keep the sample size low if population is 
a. Heterogeneous                  b. Inaccessible 
c. Homogeneous                   d. All the above
Ans: 

16. Which technique is generally followed when the population is finite? 
a. Area sampling technique                           b. Purposive sampling technique 
c. Systematic sampling technique                  d. None of the above
Ans: 

17. Cluster sampling is used when a. Population is scattered and sample size is to be kept large. b. Population is heterogeneous. c. Long survey is needed. d. Both (a) and (c)


18.  A researcher divides his population into certain groups and fixes the size of the sample from each group. It is called 
a. Stratified sample                     b. Quota sample 
c. Cluster sample                        d. All the above
Ans: 

19. Which of the following is a non-probability sample? 
a. Quota sample                                   b. Simple random sample 
c. Purposive sample                             d. Both (a) and (c)
Ans: 

20. If a researcher selected five schools at random and then interviewed each of the teachers in those five schools, the researcher used 
a. Simple random sampling               b. Stratified random sampling 
c. Cluster random sampling               d. None of the above
Ans: 

21. Which of the following terms best describes data that were originally collected at an earlier time by a different person for a different purpose? 
a. Primary data                    c. Experimental data 
b. Secondary data               d. None of the above
Ans: 

22. Which of these is not a method of data collection? 
a. Questionnaires          b. Interviews 
d. Experiments              c. Observations
Ans: 

23. Which of the following is an example of a random sampling method? 
a. Systematic sampling                    b. Convenience sampling 
c. Purposive sampling                      d. None of the above
Ans: 

24. Which of the following is not an example of a random sampling method? 
a. Systematic sampling                     b. Stratified random sampling 
c. Simple random sampling              d. All the above
Ans: 

25. Which of the following is an example of a random sampling method? 
a. Two-stage random sampling                          b. Systematic sampling 
c. Convenience sampling                                   d. Purposive sampling
Ans: 

26. Which of the following is an example of a non-random sampling method? 
a. Convenience sampling                 b. Stratified random sampling 
c. Simple random                             d. Cluster random
Ans: 

27. The purpose of stratified random sampling is to make certain that 
a. Every member of the population has an equal chance of being selected. 
b. For proportionate representation from different categories. 
c. Prompt response from respondents. 
d. None of the above
Ans: 

28. A correlation coefficient is best characterized as 
a. A measure of the extent of the relationship between two variables. 
b. An index of the causal direction between an independent and dependent variable. 
c. An indication of the likelihood that an experimental finding will be replicated by others. 
d. A measure of the likelihood that observed differences may be attributed to chance.
Ans: 

29. Responding to a substance like a sugar pill as if it were a drug is called 
a. The placebo effect.                    b. An extraneous factor 
c. Variability                                  d. None of the above
Ans: 

30. What is a cross-sectional design? 
a. A study of one specific segment of customers. 
b. The research design that is free from any personalbias. 
c. The collection of data from more than respondent in the same time period. 
d. A comparison of two or more variables over a long period of time.
Ans: 

31.