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

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

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

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

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

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: 100-200 For this study, simple random sampling would be practically impossible. Dr. K. A. Korb University of Jos

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

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

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

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

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

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

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

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

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

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

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.

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

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