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- 1. EDU702: RESEARCH METHODOLOGY THE BASIC OF EDUCATIONAL RESEARCH SAMPLING
- 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. DEFINITION: POPULATION The larger group from which individuals are selected to participate.
- 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. SAMPLING: 1) 2) RANDOM SAMPLING METHOD NONRANDOM SAMPLING METHOD
- 6. RANDOM SAMPLING METHODS 1. 2. 3. 4. Simple Random Sampling Stratified Random Sampling Cluster Random Sampling Two-Stage Random Sampling
- 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. 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. 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. 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. ADVANTAGES OF SIMPLE RANDOM SAMPLING: Easy to conduct Strategy requires minimum knowledge of the population to be sampled
- 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. 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. 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. 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. ADVANTAGES OF STRATIFIED RANDOM SAMPLING: More precise sample. Can be used both proportions and stratification sampling. Sample represents the desired strta.
- 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. CLUSTER SAMPLING The process of randomly selecting intact groups, not individuals, within the defined population sharing similar characteristics.
- 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. 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. 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. ADVANTAGES OF CLUSTER RANDOM SAMPLING: Efficient. Researcher does not need nemes of all population members. Reduces travel to site. Useful for educational research.
- 23. DISADVANTAGES OF CLUSTER RANDOM SAMPLING: Fewer sampling points make it less like that the sample is representative.
- 24. TWO-STAGE RANDOM SAMPLING The process of COMBINING Cluster Random Sampling with an Individual Random Sampling.
- 25. STEPS IN TWO-STAGE RANDOM SAMPLING: 1.
- 26. ADVANTAGES OF TWO-STAGE RANDOM SAMPLING: Less time-consuming
- 27. NONRANDOM SAMPLING METHODS 1. 2. 3. Systematic Sampling Convenience Sampling Purposive Sampling
- 28. SYSTEMATIC SAMPLING The process of selecting individuals within the defined population from a list by taking every Kth name.
- 29. 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.
- 30. 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.
- 31. ADVANTAGES OF SYSTEMATIC SAMPLING: Sample selection is simple
- 32. 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.
- 33. CONVENIENCE SAMPLING The process of including whoever happens to be available at the time . It is also called “accidental” or “haphazard” sampling.
- 34. DISADVANTAGES OF CONVENIENCE SAMPLING: Difficulty in determining how much of the effect (dependent variable) results from the cause (independent variable)
- 35. 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 “judgment” sampling.
- 36. DISADVANTAGES OF PURPOSIVE SAMPLING: Potential for inaccuracy in the researcher’s criteria and resulting sample selection.
- 37. END THANK YOU

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