1. Sampling and Participants
Dr. K. A. Korb
University of Jos

2. Outline Population Validity Sampling Methods Sample Size
Simple Random Sampling
Stratified Sampling
Cluster Sampling
Convenience Sampling
Sample Size
Dr. K. A. Korb
University of Jos

3. Population Validity
Extent that an experiment’s results can generalize beyond participants in a particular study to a larger group of people
Research Example: A descriptive study examining the extent of parents’ involvement in schools
Dr. K. A. Korb
University of Jos

4. All Nigerian parents with children in school
Parents in these two samples (government school vs. Hillcrest) will likely have different involvement in their child’s education because of many different reasons – finances, parental education, trust of school officials, etc.
The purpose of sampling validity is to make a strong argument for why the results of your study will generalize beyond those who participated in your study.
Population
All Nigerian parents with children in school
Sample
All Nigerian parents with students
in Hillcrest
Sample
All Nigerian parents with students in Government Secondary School
Dr. K. A. Korb
University of Jos

5. Simple Random Sampling
Definition: All individuals in the defined population have an equal chance of being part of the sample.
Advantage: Conclusions from the data can be generalized to the larger population
Disadvantage: Difficult to implement, so very few studies actually use simple random sampling
Dr. K. A. Korb
University of Jos

6. Simple Random Sampling Example
Population:
All Nigerian parents with children in school
Size: Millions of adults
Participants are chosen randomly either through a random number table or putting all names in a hat.
Sample:
Those randomly chosen from the population.
Size:
For this study, simple random sampling would be practically impossible.
Dr. K. A. Korb
University of Jos

7. Random Sampling vs. Random Assignment
Random Sampling: Randomly selecting those people who will participate in your study.
Allows you to generalize your findings beyond the sample of your study.
However, few educational studies can practically use random selection.
Random Assignment: Once you participants have been selected, they are randomly placed into the treatment and control groups.
Only applies to experimental design
MUST be used for an experiment to be a true experiment.
Dr. K. A. Korb
University of Jos

8. Population Sample Random Sampling
Randomly chose people from the population to be part of the research sample.
Sample
Dr. K. A. Korb
University of Jos

9. Sample Random Assignment Control Treatment Group Group
1. Names of all participants are placed in a hat
2. As names are drawn out of the hat, they are placed in alternating order into the treatment and control groups.
Treatment Group
Control
Group
Dr. K. A. Korb
University of Jos

10. Stratified Sampling
Definition: Select a sample so certain subgroups can be adequately represented
Subgroups, or stratums, are identified by demographic variables of interest to the study, such as gender, ethnicity, age, occupation, etc.
Random sampling will be used within each stratum.
Use If:
The group is heterogeneous on an important variable (e.g., ethnicity, gender). or
The purpose of the study is to compare groups of different characteristics (e.g., a causal-comparative study)
Dr. K. A. Korb
University of Jos

11. Stratified Random Sampling Example
In the research example, one research question may compare the participation of mothers to the participation of fathers in their child’s education.
To test the difference between mothers and fathers, an equal number of mothers and fathers must be selected for the sample.
Therefore, the population should first be divided into male and female, and then random selection applied within each group.
Procedure:
Determine the stratums to be sampled.
Determine the number of participants necessary for each stratum.
Randomly sample participants from within each sample.
Dr. K. A. Korb
University of Jos

12. Stratified Random Sampling Example
Population Stratum:
Fathers of children in school
Randomly chose the same number from both stratums.
Population Stratum:
Mothers of children in school
Sample
The resulting sample will have an equal number of participants from both stratums.
Dr. K. A. Korb
University of Jos

13. Cluster Sampling
Definition: Randomly sample a naturally occurring group of people
For example: A group could be a classroom of students
Advantage: Easier to conduct the study.
Disadvantage: Regular statistics CANNOT be conducted with cluster sampling.
Instead of conducting statistics on participants’ data, you have to conduct the statistics on the groups’ data.
Therefore, finding significant results is considerably more difficult.
Dr. K. A. Korb
University of Jos

14. Cluster Sampling Example
Population Groups:
Schools in Nigeria
Randomly chose the groups from the population.
Sample
The resulting sample will be analyzed based on the GROUP data.
Dr. K. A. Korb
University of Jos

15. Convenience Sampling
Definition: Selects a sample that suits the purpose of the study and is convenient.
Advantage: Practically, most of the other sampling methods are impossible to accomplish. A strategic convenience sample makes psychological and educational research possible.
Disadvantage: The researcher has to build a case in the conclusion of their paper about the group of people the study’s findings will generalize to.
Note: Virtually all educational research uses convenience sampling, perhaps with some elements of random sampling or stratified random sampling.
Dr. K. A. Korb
University of Jos

16. Convenience Sampling
When using convenience sampling, you will improve the quality of your work if you:
Specifically describe the characteristics of your sample.
Give a rationale for why the sample was appropriate for your study
Specify the population to which your results will likely generalize.
Dr. K. A. Korb
University of Jos

17. Convenience Sampling Example
Dr. K. A. Korb
University of Jos
Convenience Sampling Example
Population:
All Nigerian parents with children in school
Participants are chosen from a group that is convenient to the experimenter and relevant for the purposes of the study.
Sample
This convenience sample includes participants from four schools that are geographically close to the experimenter and schools where the experimenter personally knows the headmaster. However, the experimenter made a point to select two public and two private schools, as well as a school with mostly wealthy children, a school with mostly poor children, and two schools in between because these characteristics may influence the results of the study.

18. Sample Size General Rule: Larger samples are better
Larger samples more accurately reflect the characteristics of the general population.
Larger samples also increase your chances of getting significant results for your study because one of the values that determine statistical significance is the size of the sample.
Exception: Case studies and qualitative studies tend to use smaller sample sizes
Dr. K. A. Korb
University of Jos

19. Minimum Sample Size Descriptive Survey Research Designs
At least 100 participants in each group
Causal-Comparative Research Designs
At least 15 participants in each group to be compared
Correlational Research Designs
At least 30 participants
Experimental Research Designs
At least 15 participants in the control group and at least 15 participants in each treatment group.
Dr. K. A. Korb
University of Jos