1. Formulation of the Research Methods A. Selecting the Appropriate Design B. Selecting the Subjects C. Selecting Measurement Methods & Techniques D. Selecting Instrumentation

2. Formulation of the Research Methods E. Developing Procedures & Protocol F. Using a Pilot Study G. Selecting the Appropriate Analysis Techniques H. Developing a Timeline & Budget I. Collecting the Data

3. Sampling Procedures

4. Definitions Population – group of things (people) having one or more common characteristics Sample – representative subgroup of the larger population Used to estimate something about a population (generalize) Must be similar to population on characteristic being investigated

5. Representative

6. Principle of Sampling AgeAV A18 21,5 B20 C23 D24 Select to a sample of two individuals to make an estimate of the average age AgeAV A18 19 B20 AgeAV A18 20,5 C23 AgeAV A18 21,5 D24 AgeAV C23 24, D24 AgeAV B20 21,5 C23 AgeAV B20 22,5 D23 In educational research: A, B, C, and D can be clases while ages can be the achievement average

7. Principle of Sampling (1) SampleSample Average (Sample Statistics) (1) Population Mean (Population Parameter) (2) Difference Between (1) and (2) 119,0 21,5 -2,5 220,5 21,5 -1,5 321,5 0 4 0 522,5 21,5 +1 624 21,5 +1,5 Conclusion:

8. Principle of Sampling AgeAV A18 21,5 B20 C23 D24 Select to a sample of three individuals to make an estimate of the average age AgeAV A18 20,33 B20 C23 AgeAV A18 21,0 B20 D24 AgeAV A18 22,0 C23 D24 AgeAV B20 22,67 C23 D24 In educational research: A, B, C, and D can be clases while ages can be the achievement average

9. Principle of Sampling (2) SampleSample Average (Sample Statistics) (1) Population Mean (Population Parameter) (2) Difference Between (1) and (2) 120,33 21,5 -1,17 221,0 21,5 -0,5 322,0 21,5 +0,5 422,67 21,5 +1,17 Conclusion:

10. Principle of Sampling (3) AgeAV A18 28 B24 C30 D40 Select to a sample of two individuals to make an estimate of the average age AgeAV A18 21 B24 AgeAV A18 24 C30 AgeAV A18 26 D40 AgeAV C30 35 D40 AgeAV B24 27 C30 AgeAV B24 32 D40 In educational research: A, B, C, and D can be clases while ages can be the achievement average

11. Principle of Sampling (3) SampleSample Average (Sample Statistics) (1) Population Mean (Population Parameter) (2) Difference Between (1) and (2) 121 28 -7 224 28 -4 326 28 -2 427 28 532 28 +4 635 28 +7 Conclusion:

13. Sampling Methods Probability Sampling Simple random sampling Stratified random sampling Systematic sampling Cluster (area) sampling Multistage sampling Non-Probability Sampling Deliberate (quota) sampling Convenience sampling Purposive sampling

14. Simple Random Sampling Equal probability Techniques  Fishbowl (with replacement & w/o replacement)  Table of random numbers Advantage  Most representative group Disadvantage  Difficult to identify every member of a population

15. Stratified Random Sampling Technique  Divide population into various strata  Randomly sample within each strata  Sample from each strata should be proportional Advantage  Better in achieving representativeness on control variable Disadvantage  Difficult to pick appropriate strata  Difficult to ID every member in population Is student of SMA 5 impression about chemistry/bio influenced by their grade?

16. Systematic Sampling Technique  Use “system” to select sample (e.g., every 5th item in alphabetized list, every 10th name in phone book) Advantage  Quick, efficient, saves time and energy Disadvantage  Not entirely bias free; each item does not have equal chance to be selected  System for selecting subjects may introduce systematic error  Cannot generalize beyond pop actually sampled

17. Cluster (Area) Sampling Randomly select groups (cluster) – all members of groups are subjects Appropriate when  you can’t obtain a list of the members of the population  have little knowledge of pop characteristics  Pop is scattered over large geographic area

18. Cluster (Area) Sampling Advantage  More practical, less costly Conclusions should be stated in terms of cluster (sample unit – school) Sample size is # of clusters

19. Multistage Sampling Stage 1  randomly sample clusters (schools) Stage 2  randomly sample individuals from the schools selected

20. Sampling Methods Probability Sampling Simple random sampling Stratified random sampling Systematic sampling Cluster (area) sampling Multistage sampling Non-Probability Sampling Deliberate (quota) sampling Convenience sampling Purposive sampling

21. Deliberate (Quota) Sampling Similar to stratified random sampling Technique  Quotas set using some characteristic of the population thought to be relevant  Subjects selected non-randomly to meet quotas (usu. convenience sampling) Disadvantage  selection bias  Cannot set quotas for all characteristics important to study

22. Convenience Sampling “Take them where you find them” - nonrandom Intact classes, volunteers, survey respondents (low return), a typical group, a typical person Disadvantage: Selection bias Use post hoc analysis to show groups were equal at the start

23. Purposive Sampling Purposive sampling (criterion-based sampling)  Establish criteria necessary for being included in study and find sample to meet criteria Solution: Screening  Use random sampling to obtain a representative sample of larger population and then those subjects that are not members of the desired population are screened or filtered out  EX: want to study smokers but can’t identify all smokers

24. Sample Size Critical factor is whether sample is representative Necessary sample size depends on population size Recommendations:  Use tables from books  30 per group  Descriptive studies – 10-20% of population  No more than 50% of population Statistical power Attrition

25. Other Sampling Considerations Random assignment Sampling of treatments (experimental research) Use post hoc analysis to show groups were equal at the start Since random sampling is often impossible, sample must be selected on some theoretical basis Be careful with generalizations

26. When Selecting Subjects … Are subjects with special characteristics necessary for your research? (age, gender, trained/untrained, expert/novice, size, etc.) Can you obtain the necessary permission and cooperation from the subjects? Can you find enough subjects? Interaction among selection of subjects, treatments, and measures is essential for experimental studies.

27. Reporting Subjects State how many subjects were selected Describe how the subjects were selected Discuss whether any subjects were lost during the study and why Explain why the subjects were selected Describe subject characteristics that are pertinent to study – be very specific Identify procedures taken to protect the subjects