Introduction to Sampling and Its Types.pptx

This presentation focus on sampling and its types and other related terms.

1. Qualitative research PRACTICAL RESEARCH 1

2. Unit V UNDERSTANDING DATA AND WAYS TO SYSTEMATICALLY COLLECT DATA

3. topics

4. LESSON 2 DESCRIPTION OF SAMPLING AND DATA COLLECTION

5. SUBJECTS, RESPONDENTS, INFORMATIONS, AND PARTICIPANTS The four terms, all common in research studies, refer to individuals who agree to become part of a research study. The term, however, reflects a distinct way that an individual participates in a research study and the type of relationship formed between the individual and the investigator.

6. SUBJECTS, RESPONDENTS, INFORMATIONS, AND PARTICIPANTS

7. SUBJECTS, RESPONDENTS, INFORMATIONS, AND PARTICIPANTS

8. SUBJECTS, RESPONDENTS, INFORMATIONS, AND PARTICIPANTS

9. WHAT IS SAMPLING? Sampling – refers to the method or process of selecting respondents or people to answer questions meant to yield data for a research study.

10. WHAT IS Sample? Sample – any sub-aggregate drawn from the population or it is a portion of a population ( Fergurson , 1973). It constitute the chosen ones through which you will derive facts and evidence to support the claims or conclusions propounded by your research problem.

11. WHAT IS POPULATION? Population - the bigger group from where you choose the sample. Any group of individuals who has one or more characteristics in common that are of interest to the researcher.

12. WHAT IS SAMPLING FRAME? Sampling Frame – the term used to mean the list of the members of such population from where you will get the sample. (Paris 2013)

13. HISTORY OF SAMPLING The beginning of sampling could be traced back to the early political activities of the Americans in 1920 when the Literary Digest did a pioneering survey about the American citizen’s favorite among the 1920 presidential candidates. This was the very first survey that served as the impetus for the discovery by academic researchers of other sampling strategies that they categorized into two classes: probability sampling or unbiased sampling and non-probability sampling . (Babbie 2013)

14. SAMPLING ERROR A sampling error crops up if the selection does not take place in the way it is planned. Such sampling error is manifested by strong dissimilarity between the sample and the ones listed in the sampling frame. The smaller the sample is, the bigger the number of sampling errors. Thus, choose to have a bigger sample of respondents to avoid sampling errors.

15. Two TYPES OF SAMPLING Probability Sampling or Unbiased Sampling Non-Probability Sampling

16. Two TYPES OF SAMPLING Probability Sampling or Unbiased Sampling It involves all members listed in the sampling frame representing a certain population focused on by your study. An equal chance of participation in the sampling or selection process is given to every member listed in the sampling frame.

17. TYPES OF SAMPLING B. Non-probability Sampling Disregards random selection of subjects. The subjects are chosen based on their availability or the purpose of the study, and in some cases, on the sole discretion of the researcher. Not all elements in the population frame have an equal chance of being selected. (Edmond 2013)

18. Types of Probability Sampling Simple Random Sampling The best type of probability sampling that uses pure chance selection. Every member have the same opportunity to be in the sample. It has two methods: a) Fishbowl Technique and b) Table of Random Numbers

19. Types of Probability Sampling Two ways of Simple Random Sampling a) Have a list of all members of the population; write each name on a card and choose cards through a pure-chance selection ( fishbowl technique/lottery sampling ). b) Have a list of all members; give a number to member and then use randomized or unordered numbers in selecting names from the list ( Table of Random Numbers ).

20. Types of Probability Sampling a.1 . Lottery sampling - also called the fishbowl technique (Fox, 1969). This procedure can be applied by first assigning numbers to the participants of your population assembling them in a sample frame. Then write the numbers of the participants in small pieces of papers, one number to a piece. Next, roll this small pieces of papers and put them in a container big enough to allow the rolled pieces to move freely in all direction. Now having shaken the box thoroughly, you pick the desired number of participants from the container. Take note, that shaking of the container should continue up to the time you reach the required number of your sample.

21. Types of Probability Sampling a.2 . Table of Random Numbers . This technique uses columns or rows, of numerical digits which were mechanically generated. In selecting sample units, the digits to be used in the table should be equal to the digits of the population. Samples are selected by taking the digits in the column or row which are equal or less than the total number of the population. A number is taken just once since each population has unique assigned number. Several columns or rows can be used until the required number of samples is reached. The table of random numbers is very useful when the population from which the sample will be drawn is unique large.

22. Types of Probability Sampling 2. Systematic Sampling - a strategy for selecting the numbers of a sample that allows only chance and “system” to determine membership in the sample. A system is a planned strategy for selecting members after a starting point is selected at random, such as every 5th subject, every 10th subject, etc. ( Vockell , 1983).

23. Types of Probability Sampling For instance, if you want to have a sample of 150, you may select a set of numbers like 1 to 15, and out of a list of 1,500 students, take every 15th name on the list until you complete the total number of respondents to constitute your sample.

24. Types of Probability Sampling 3. Stratified Sampling - The group comprising the sample is chosen in a way that such group is liable to subdivision during the data analysis stage. A study needing group-by-group analysis finds stratified sampling the right probability sampling to use.

25. Types of Probability Sampling In this strategy your target population is first divided into groups each belonging to the same stratum. This is to avoid the possibility of getting samples from another stratum. But to be effective in your stratified sampling the participants within each of the strata should be selected at random. This is known as stratified random sampling.

26. Types of Probability Sampling 4. Cluster Sampling - This is a probability sampling isolate a set or cluster of persons instead of individual members to serve as sample members.

27. Types of Probability Sampling For example, if you want to have a sample of 120 out of 1,000 students, you can randomly select three sections with 40 students each to constitute the sample.

28. Types of Non-probability Sampling 1. Quota Sampling – a type of non-probability sampling that uses a quota or a specific set of persons who have the characteristics of the target population involved in the study characteristics.

29. Types of Non-probability Sampling For instance, you are required in a research class to determine the most favored soft drinks from a population of televiewers, you should interview televiewers who drink soft drinks. You continue this process until you arrive at your quota. Because of the quota you have set, you certainly will neglect other participants’ opinion regarding the soft drinks they favor most. Thus, data you have collected cannot surely be considered as representing the opinions of the population.

30. Types of Non-probability Sampling 2. Voluntary Sampling - the subjects are the ones volunteering to constitute the sample.

31. Types of Non-probability Sampling 3. Purposive or Judgmental Sampling - A type of non-probability sampling wherein the researcher chooses people who could correspond and meet the objectives or purpose of the study .

32. Types of Non-probability Sampling 4. Availability Sampling - A type of non-probability sampling wherein the respondents of the study are the ones who are available and showed willingness to participate on the study.

33. Types of Non-probability Sampling 5. Snowball Sampling - this sampling method does not give a specific set of samples . The researcher have the freedom to increase the number of people they want to form the sample of your study. (Harding 2013)

34. Sampling in Qualitative Qualitative is more flexible compared to quantitative in terms of sampling. Sampling techniques are suggestive than prescriptive. Could be more creative in sampling.

35. assessment 1. This term is used in survey research as individuals asked to respond to very specific questions. Subjects Respondents Informants Participants

36. assessment 2. This individuals is used in an experimental-type research that denotes passive roles. Subjects Respondents Informants Participants

37. assessment 3. It refers to the method or process of selecting respondents. Sample Sampling Sampling Frame Population

38. assessment 4. It refers to the chosen ones, a portion of the population that would best represent individuals in the study. Sample Sampling Sampling Frame Population

39. assessment 5. The beginning of sampling could be traced back to the early political activities of the Americans in _____. 1915 1920 1930 1940

40. assessment 6. A type of sampling that involves all members listed in the sampling frame representing a certain population focused on by your study. Probability Sampling Non-probability Sampling

41. assessment 7. A type of sampling wherein subjects are chosen based on their availability or the purpose of the study, and in some cases, on the sole discretion of the researcher. Probability Sampling Non-probability Sampling

42. assessment 8. A strategy for selecting the numbers of a sample that allows only chance and system to determine membership in the sample. Simple Random Sampling Systematic Sampling Stratified Sampling Cluster Sampling

43. assessment 9. The best type of probability sampling that uses a pure-chance selection. Simple Random Sampling Systematic Sampling Stratified Sampling Cluster Sampling

44. assessment 10. This is a probability sampling that makes you isolate a set of persons instead of individual members to serve as sample members. Simple Random Sampling Systematic Sampling Stratified Sampling Cluster Sampling

45. assessment 11. A type of non-probability sampling wherein the subject's volunteers to constitute a sample. Quota Sampling Voluntary Sampling Purposive Sampling Snowball Sampling