RC 04 sampling procedure and sample.pptx

sampling

1. sampling procedure and sample

2. Making Words Meaningful Directions: Choose the letter of the word that corresponds in meaning to the italicized word in the sentence. Be guided by the contextual clues.

3. 1. Name the islands that constitute the town of Hundred Islands in Pangasinan. a. represent c. compose b. advertise d. popularize

4. 2. The cabinet members are ready to tackle issues propounded by the businessmen. a. questioned c. contrasted b. forwarded for mailing d. presented

5. 3. Please categorize the books based on subject area. a. classify c. mark b. count d. arrange 4. Her religiosity was manifested by her regular attending of Holy Mass. a. pictures c. stressed b. shown d. signaled

6. 5. Give him more time to mull over your proposal. a. remember c. criticize b. question d. ponder

7. 6. Students getting grades of 75, 82, 88, 92, and 96 belong to a heterogeneous group; the same grade of 95–96, to a homogenous group. a. varied abilities c. same abilities b. little ability d. zero ability

8. In research, what do you know about sampling? What do you like to know in research sampling?

9. Test: Write the letter of the expression in the box that corresponds to the expression outside the box. 1. List of names representing the target population Sampling error g. 1920 Literary Digest Quota sampling h. population Sampling frame i . probability sampling Money j. snowballing Cluster sampling k. whole – nation subject Stratified sampling

10. 2. Origin of sample Sampling error g. 1920 Literary Digest Quota sampling h. population Sampling frame i . probability sampling Money j. snowballing Cluster sampling k. whole – nation subject Stratified sampling

11. 3. Dissimilarity of sample with those in the sampling frame Sampling error g. 1920 Literary Digest Quota sampling h. population Sampling frame i . probability sampling Money j. snowballing Cluster sampling k. whole – nation subject Stratified sampling

12. 4. Requires a big sample size Sampling error g. 1920 Literary Digest Quota sampling h. population Sampling frame i . probability sampling Money j. snowballing Cluster sampling k. whole – nation subject Stratified sampling

13. 5. Randomized sample Sampling error g. 1920 Literary Digest Quota sampling h. population Sampling frame i . probability sampling Money j. snowballing Cluster sampling k. whole – nation subject Stratified sampling

14. 6. Intentional choosing of sample Sampling error g. 1920 Literary Digest Quota sampling h. population Sampling frame i . probability sampling Money j. snowballing Cluster sampling k. whole – nation subject Stratified sampling

15. 7. No specific number of respondents Sampling error g. 1920 Literary Digest Quota sampling h. population Sampling frame i . probability sampling Money j. snowballing Cluster sampling k. whole – nation subject Stratified sampling

16. 8. Hindrance to big sample Sampling error g. 1920 Literary Digest Quota sampling h. population Sampling frame i . probability sampling Money j. snowballing Cluster sampling k. whole – nation subject Stratified sampling

17. 9. Group-by-group selection of sample Sampling error g. 1920 Literary Digest Quota sampling h. population Sampling frame i . probability sampling Money j. snowballing Cluster sampling k. whole – nation subject Stratified sampling

18. 10. Uses sub-groups Sampling error g. 1920 Literary Digest Quota sampling h. population Sampling frame i . probability sampling Money j. snowballing Cluster sampling k. whole – nation subject Stratified sampling

19. Definition S ampling is a word that refers to your method or process of selecting respondents or people to answer questions meant to yield data for a research study.

20. The chosen ones constitute the sample through which you will derive facts and evidence to support the claims or conclusions propounded by your research problem.

21. The bigger group from where you choose the sample is called population , and sampling frame is the term used to mean the list of the members of such population from where you will get the sample. (Paris 2013)

22. 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.

23. (P) How numerous the sampling errors are depends on the size of the sample. 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.

24. However, deciding to increase the size of your sample is not so easy. There are these things you have to mull over in finalizing about this such as expenses for questionnaires and interview trips, interview schedules, and time for reading respondents’ answers.

25. The right sample size also depends on whether or not the group is heterogeneous or homogeneous. The first group requires a bigger size; the second, a smaller one.

26. Types of sampling: 1. Probability sampling or unbiased sampling 2. Non-probability sampling. (Babbie 2013)

27. TYPES OF SAMPLING 1. PROBABILITY SAMPLING—the sample is selected by means of some systematic way in which every element of the population has a chance of being included in the sample.

28. 2. NON-PROBABILITY SAMPLING --The sample is not a proportion of the population and there is no system in selecting the sample.

29. activity: discuss and give example of each types of probability sampling and non – probability sampling.

30. Types of Probability Sampling 1. Simple Random Sampling 2. Systematic Sampling 3. Stratified Sampling 4. Cluster Sampling

31. Types of Non-Probability Sampling 1. Quota Sampling 2. Voluntary Sampling 3. Purposive or Judgmental Sampling 4. Availability Sampling 5. Snowball Sampling

32. Types of Probability Sampling 1. Simple Random Sampling 2. Systematic Sampling 3. Stratified Sampling 4. Cluster Sampling

33. 1. Simple Random Sampling Simple random sampling is the best type of probability sampling through which you can choose sample from a population. Using a pure-chance selection, you assure every member the same opportunity to be in the sample.

34. Here, the only basis of including or excluding a member is by chance or opportunity, not by any occurrence accounted for by cause-effect relationships. Simple random sampling happens through any of these two methods: (Burns 2012)

35. Have a list of all members of the population; write each name on a card, and choose cards through a pure-chance selection. 2) Have a list of all members; give a number to member and then use randomized or unordered numbers in selecting names from the list.

36. 2. Systematic Sampling For this kind of probability sampling, chance and system are the ones to determine who should compose the sample.

37. 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.

38. 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.

39. 4. Cluster Sampling This is a probability sampling that makes you isolate a set of persons instead of individual members to serve as sample members.

40. 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.

41. Non-Probability Sampling 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.

42. This is not a scientific way of selecting respondents. Neither does it offer a valid or an objective way of detecting sampling errors. (Edmond 2013)

43. Types of Non-Probability Sampling 1. Quota Sampling 2. Voluntary Sampling 3. Purposive or Judgmental Sampling 4. Availability Sampling 5. Snowball Sampling

44. 1. Quota Sampling You resort to quota sampling when you think you know the characteristics of the target population very well. In this case, you tend to choose sample members possessing or indicating the characteristics of the target population.

45. Using a quota or a specific set of persons whom you believe to have the characteristics of the target population involved in the study is your way of showing that the sample you have chosen closely represents the target population as regards such characteristics.

46. 2. Voluntary Sampling Since the subjects you expect to participate in the sample selection are the ones volunteering to constitute the sample, there is no need for you to do any selection process.

47. 3. Purposive or Judgmental Sampling You choose people whom you are sure could correspond to the objectives of your study, like selecting those with rich experience or interest in your study.

48. 4. Availability Sampling The willingness of a person as your subject to interact with you counts a lot in this non-probability sampling method.

49. If during the data-collection time, you encounter people walking on a school campus, along corridors, and along the park or employees lining up at an office, and these people show willingness to respond to your questions, then you automatically consider them as your respondents.

50. 5. Snowball Sampling Similar to snow expanding widely or rolling rapidly, this sampling method does not give a specific set of samples. This is true for a study involving unspecified group of people.

51. Dealing with varied groups of people such as street children, mendicants, drug dependents, call center workers, informal settlers, street vendors, and the like is possible in this kind of non-probability sampling.

52. Free to obtain data from any group just like snow freely expanding and accumulating at a certain place, you tend to increase the number of people you want to form the sample of your study. (Harding 2013)

53. What are the types of probability sampling? Describe each type? How about the types of non – probability sampling?

54. In your current research study, what type of sampling technique will be the best for your topic? Explain?

55. Directions : Write P if the sentence talks about probability sampling; otherwise, write NP for non – probability sampling. 1. Checking every 10th student in the list 2. Interviewing some persons you meet on the campus 3. Dividing 100 persons into groups

56. 4. Choosing subjects behaving like the majority members of NPC Town 5. Choosing a group of subjects among several groups 6. Choosing subjects capable of helping you meet the aim of your study

57. 7. Choosing samples by chance but through an organizational pattern 8. Letting all members in the population join the selection process 9. Having people willing to be chosen as respondents 10. Matching people’s traits with the population members’ traits