1. Sampling Dr Hidayathulla Shaikh

2. Contents At the end of lecture student should know  Why sampling is done  Terminologies involved  Different Sampling methods  Conclusion.

3. Introduction Sampling is very often used in our daily life. For example, while purchasing food grains from a shop we usually examine a handful from the bag to assess the quality of the commodity.

4. A doctor examines a few drops of blood as sample and draws conclusion about the blood constitution of the whole body. Thus most of our investigations are based on samples.

5. Terminologies  Population  The entire group under study as defined by research objectives. Sometimes called the “universe.”  Sample  A subset of the population that should represent the entire group.

6. What is Sampling?  Sampling is a process by which we study a small part of a population to make judgments about the entire population..  The process of selecting a subgroup of a population to represent the entire population. (Research methods glossary)  Knowing Whole from Its Part

7. Classification of sampling methods  Probability samples: Are those in which members of the population have a known chance (probability) of being selected.  Non-probability samples: Instances in which the chances (probability) of selecting members from the population are unknown.

8. Classification of Sampling Techniques Sampling Techniques Nonprobability Sampling Techniques Probability Sampling Techniques Convenience Sampling Judgmental Sampling Quota Sampling Snowball Sampling Systematic Sampling Stratified Sampling Cluster Sampling Other Sampling Techniques Simple Random Sampling

9. PROBABILITY SAMPLING METHODS SIMPLE RANDOM SAMPLING The probability of being selected is “known and equal” for all members of the population. Done when population is small, readily available and homogenous Blind Draw Method (e.g. names “placed in a hat” and then drawn randomly)

11. Methods of selection of a simple random sampling a) Lottery Method:  This is the most popular and simplest method.  All the items of the population are numbered on separate slips of paper of same size, shape and color, folded and mixed up in a container.  The required numbers of slips are selected at random for the desired sample size. For eg, if we want to select 5 students out of 50, then we must write their names or roll numbers of all 50 students on slips & mix them and make a random selection of 5 students.

12. b) Table of Random numbers: As the lottery method cannot be used, when the population is infinite, the alternative method is that of using the table of random numbers.

13.  How to use a random number table.  Let's assume that we have a population of 185 students and each student has been assigned a number from 1 to 185.  Suppose we wish to sample 5 students (although we would normally sample more, we will use 5 for this example).  Since we have a population of 185 and 185 is a three digit number, we need to use the first three digits of the numbers listed on the chart.

14. We close our eyes and randomly point to a spot on the chart. For eg, assume that we selected 20631 in the first column. Interpret that number as 206 (first three digits). Since we dont have a member of our population with that number, we go to the next number 899 (89990). Once again we don't have someone with that number, so we continue at the top of the next column. As we work down the column, we find that the first number to match our population is 100 (actually 10005 on the chart). Student no. 100 would be in the sample. Continuing down the chart, we see that the other four subjects in our sample would be students 049, 082, 153, and 005.

15. c ) Random number selections using calculators or computers: Random number can be generated through scientific calculator or computers. For each press of the key get a new random numbers. The ways of selection of sample is similar to that of using random number table.

16. Systematic Sampling The sample is chosen by selecting a random starting point and then picking every nth element in succession from the sampling frame. This method is at times more efficient than simple random sampling.

18.  A systematic sample is to be selected from 1200 students of a school.  The sample size selected is 100.  The sampling interval is, therefore, 1200/ 100= 12.  The number of the first student to be included in the sample is chosen randomly, for e.g., by blindly picking 1 out of 12 pieces of paper, numbered 1- 12. If number 6 is picked, then every 12 th student will be included in the sample, starting with student number 6, until 100 students are selected.  Then numbers selected would be 6, 18, 30, 42 and so on.

19. Cluster Sampling Method by which the population is divided into groups (clusters), such as cities, villages, street blocks, any of which can be considered a representative sample. E.g.:Area sampling Then a random sample of clusters is selected, based on a probability sampling technique such as simple random sampling. For each selected cluster, either all the elements are included in the sample (one-stage) or a sample of elements is drawn probabilistically (two-stage).

21. Stratified Sampling Method  Used when the population distribution of items are skewed or heterogenous.  Allows us to draw a more representative sample.

22.  If it is important that the sample includes representative groups of study units with specific characteristics.  For e.g., residents from urban and rural areas, or different age groups.  Then the sampling frame must be divided into groups or strata, according to these characteristics.  Random or systematic samples of predetermined size will then have to be obtained from each group (stratum).  This is called Stratified Sampling.

23. The population is separated into homogeneous groups/segments/strata and a sample is taken from each. The results are then combined to get the picture of the total population.

24. Nonprobability Sampling Methods

25. Convenience Sampling Method Samples drawn at the convenience of the interviewer. Often, respondents are selected because they happen to be in the right place at the right time. use of students, and members of social organizations mall intercept interviews without qualifying the respondents “people on the street” interviews

26. Judgment Sampling Method Samples that require a judgment or an “educated guess” on the part of the interviewer as to who should represent the population. Also, “judges” (informed individuals) may be asked to suggest who should be in the sample.

27. Quota Sampling Methods Samples that set a specific number of certain types of individuals to be interviewed. Often used to ensure that convenience samples will have desired proportion of different respondent classes. Usually done to include a particular segment of population.

28. In snowball sampling, an initial group of respondents is selected, usually at random.  After being interviewed, these respondents are asked to identify others who belong to the target population of interest.  Subsequent respondents are selected based on the referrals. Snowball/ Referral Sampling

29. Conclusion  Normally one should resort to a simple random sampling because under it bias can be eliminated generally and sampling error can be estimated.  In situations where simple random sampling cannot be used, other sampling methods should be considered.  At times, several methods of sampling may well be used in the same study.