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The basic of educational research sampling

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The basic of educational research sampling

1. 1. EDU702: RESEARCH METHODOLOGY THE BASIC OF EDUCATIONAL RESEARCH SAMPLING
2. 2. DEFINITION: SAMPLING The process of selecting a number of individuals for a study in such a way that the individuals represent the larger group from which they were selected.
3. 3. DEFINITION: POPULATION The larger group from which individuals are selected to participate.
4. 4. TARGET VERSUS ACCESSIBLE POPULATIONS: 1. The Target Population is the ideal selection of actual population which researcher really like to generalize: - is rarely available. - Researcher’s ideal choice. 2. The Accessible or ‘available’ population is the population to which a researcher is able to generalize: - Researcher’s realistic selection
5. 5. SAMPLING: 1) 2) RANDOM SAMPLING METHOD NONRANDOM SAMPLING METHOD
6. 6. RANDOM SAMPLING METHODS 1. 2. 3. 4. Simple Random Sampling Stratified Random Sampling Cluster Random Sampling Two-Stage Random Sampling
7. 7. SIMPLE RANDOM SAMPLING The proces of selecting a sample that allows induvidual in the defined population to have an equal and independent chance of being selected for the sample.
8. 8. STEPS IN RANDOM SAMPLING: 1. Identify and define the population. 2. Determine the desired sample size. 3. List all members of the population. 4. Assign all individuals on the list consecutive number from zero to the required number. Each individual must have the same number of digits as each other individual.
9. 9. STEPS IN RANDOM SAMPLING: 5. Select an arbitrary number in the table of random numbers. 6. For the selected number, look only at the number of digits assigned to each population member.
10. 10. STEPS IN RANDOM SAMPLING: 7. 8. If the number corresponds to the number assigned to any of the individual in the population, then that individual is included in the sample. Go to the next number in the column and repeat step #7 until the desired number of individuals has been selected for the sample.
11. 11. ADVANTAGES OF SIMPLE RANDOM SAMPLING:  Easy to conduct  Strategy requires minimum knowledge of the population to be sampled
12. 12. DISADVATAGES OF SIMPLE RANDOM SAMPLING:  Need names of all population members.  May over-represent or under-estimate sample members.  There is difficulty in reaching all selected in the sample.
13. 13. STRATIFIED RANDOM SAMPLING The process of selecting a sample that allows identified subgroups in the defined population to be represented in the same proportion that they exist in the population.
14. 14. STEPS IN STRATIFIED SAMPLING: 1. Identify and define the population. 2. Determine the desired sample size. 3. Identify the variable and subgroups (strata) for which you want to guarantee appropriate, equal representation.
15. 15. STEPS IN STRATIFIED RANDOM SAMPLING 4. Classify all members of the population as members of the one identified subgroup. 5. Randomly select, using a table of random numbers; an “appropriate” number of individuals from each of the subgroups, appropriate meaning an equal number of individuals.
16. 16. ADVANTAGES OF STRATIFIED RANDOM SAMPLING:  More precise sample.  Can be used both proportions and stratification sampling.  Sample represents the desired strta.
17. 17. DISADVANTAGES OF STRATIFIED RANDOM SAMPLING:  Need names of all population members.  There is difficulty in reaching all selected in the sample.  Researcher must have names of all populations.
18. 18. CLUSTER SAMPLING The process of randomly selecting intact groups, not individuals, within the defined population sharing similar characteristics.
19. 19. STEPS IN CLUSTER RANDOM SAMPLING: 1. Identify and define the population. 2. Determine the desired sample size. 3. Identify and define a logical cluster.
20. 20. STEPS IN CLUSTER RANDOM SAMPLING: 4. List all clusters (or obtain a list) that make up the population of clusters. 5. Estimate the average number of population members per cluster. 6. Determine the number of clusters needed by dividing the sample size by the estimated size of a cluster.
21. 21. STEPS IN CLUSTER RANDOM SAMPLING: 7. Randomly select the needed number of clusters by using a table of random numbers. 8. Include in your study all population members in each selected cluster.
22. 22. ADVANTAGES OF CLUSTER RANDOM SAMPLING: Efficient.  Researcher does not need nemes of all population members.  Reduces travel to site.  Useful for educational research. 
23. 23. DISADVANTAGES OF CLUSTER RANDOM SAMPLING:  Fewer sampling points make it less like that the sample is representative.
24. 24. TWO-STAGE RANDOM SAMPLING The process of COMBINING Cluster Random Sampling with an Individual Random Sampling.
25. 25. STEPS IN TWO-STAGE RANDOM SAMPLING: 1. Select randomly 25 schools from 100 schools in the district. (Cluster)
26. 26. ADVANTAGES OF TWO-STAGE RANDOM SAMPLING:  Less time-consuming
27. 27. DEFINITION OF NON RANDOM SAMPLING  Any sampling method where some elements of the population have no choice of selection or where the probability of selection cannot be accurately determined.
28. 28. TYPES OF NON RANDOM SAMPLING METHODS 1. 2. 3. Systematic Sampling Convenience Sampling Purposive Sampling
29. 29. SYSTEMATIC SAMPLING The process of selecting individuals within the defined population from a list by taking every Kth name. **K = sampling interval (sometimes known as the skip)
30. 30. STEPS IN SYSTEMATIC SAMPLING: 1. Identify and define the population. 2. Determine the desired sample size. 3. Obtain a list of the population. 4. Determine what K is equal to by dividing the size of the population by the desired sample size.
31. 31. Equation K= N n K = sampling interval N = population size n = sample size
32. 32. STEPS IN SYSTEMATIC SAMPLING: 5. Start at some random place in the population list. Close your eyes and point your finger to a name. 6. Starting at that point, take every Kth name on the list until the desired sample size is reached. 7. If the end of the list is reached before the desired sample is reached, go back to the top of the list.
33. 33. ADVANTAGES OF SYSTEMATIC SAMPLING:  Sample selection is simple
34. 34. DISADVANTAGES OF SYSTEMATIC SAMPLING:  All members of the population do not have an equal chance of being selected.  The Kth person may be related to a periodical order in the population list, producing unrepresentativeness in the sample.
35. 35. CONVENIENCE SAMPLING The process of including whoever happens to be available at the time . It is also called “accidental” or “haphazard” sampling.
36. 36. ADVANTAGE OF CONVENIENCE SAMPLING:  the availability and the quickness with which data can be gathered
37. 37. DISADVANTAGES OF CONVENIENCE SAMPLING:  Difficulty in determining how much of the effect (dependent variable) results from the cause (independent variable)  the risk that the sample might not represent the population as a whole, and it might be biased by volunteers
38. 38. PURPOSIVE SAMPLING The process whereby the researcher selects a sample based on experience or knowledge of the group to be sampled. It is also called “judgement” sampling.
39. 39. ADVANTAGE OF PURPOSIVE SAMPLING Useful for situations where you need to reach a targeted sample quickly and where sampling for proportionality is not the main concern.
40. 40. DISADVANTAGES OF PURPOSIVE SAMPLING:  Potential for inaccuracy in the researcher’s criteria and resulting sample selection.
41. 41. Identify Types of Sampling A. B. C. D. E. F. G. Simple random sampling Stratified random sampling Cluster sampling Two-stage random sampling Convenience sampling Purposive sampling No sampling—entire population is being studied.
42. 42.  1._____ A researcher is interested in interviewing a group of New York City police officers. She goes to the main precinct in Manhattan and asks for volunteers to be interviewed. The researcher then pays for the interviews.  2._____ A researcher is interested in interviewing all the members of the New York City police force who do not live in the city. He gets a roster of the names of all officers on the force, randomly selects five police stations, and then conducts interviews of all officers in those stations.
43. 43. 3._____ A researcher is interested in interviewing alumni of San Simeon College who graduated between the years 1990 and 1996. He gets the roster of the names of these individuals from the alumni office and mails a questionnaire to everyone on this roster. 4._____ Another researcher is also interested in interviewing alumni of San Simeon College who graduated between the years 1990 and 1996. He gets the roster of the names of these individuals from the alumni office, selects the names of 100 individuals who graduated during these years using a table of random numbers, and then mails a questionnaire to everyone selected.
44. 44.  5._____ A researcher is interested in identifying the attitudes of the physicians who work for Keyser Hospital toward the Republican plan for health care. She obtains a list of all the Keyser Medical Centers in Southern California and randomly selects ten of these Centers. Then she obtains a list of all the physicians at these Centers and randomly selects eight physicians from each Center to interview.  6._____ A graduate student enrolled in the Marriage and Family Counseling Program at Daytona University is interested in determining how other graduate students feel about the program. He interviews all of the students he has access to on a given Monday night when he takes one of his counseling courses.
45. 45.  7._____ A student enrolled in the Hotel and Restaurant Management School at Colorado State is researching the best restaurants in Denver based on the opinions of food critics. She begins by asking her advisor who refers the student to four food critics who have written extensively on the subject and whom the student then contacts to interview for her study.
46. 46. END THANK YOU 