Overview
This lecture covers the fundamentals of sampling techniques in research, including definitions, types of sampling methods, and key considerations for sample selection and data collection.
Key Concepts in Sampling
- A sample is a subset of a population selected for research purposes.
- The population is the total group from which a sample may be drawn (e.g., all athletes).
- The target population is the group you want to generalize your results to.
- The accessible population is the group you can realistically reach or collect data from.
- A sampling frame is the list of all potential subjects in the population.
- A subject or case is a specific individual from the sample.
- Sampling technique refers to the method used to select a sample from the population.
Steps in the Sampling Process
- Define the target population.
- Select the sampling frame and method.
- Determine the sample size.
- Collect data from the sample.
- Assess the response rate (number of responses divided by total contacted).
Probability Sampling Methods
- Simple Random Sampling: Every individual has an equal chance of being selected; best for small, homogeneous populations.
- Stratified Sampling: Population is divided into strata (subgroups); random samples are taken from each subgroup in proportion to their size.
- Systematic Sampling: Selects every nth individual from a list after a random start; the interval depends on the desired sample size.
- Cluster Sampling: Randomly selects groups (clusters), then samples all or some individuals within clusters; useful for large, geographically spread populations.
- Multi-stage Sampling: Combines several sampling methods in stages, narrowing the population at each step.
Non-Probability Sampling Methods
- Quota Sampling: Ensures the sample reflects certain characteristics in proportion to the population (e.g., by nationality).
- Snowball Sampling: Current subjects refer researchers to additional subjects, expanding the sample network.
- Judgment (Purposive) Sampling: Researcher selects participants based on their knowledge or judgment.
- Convenience Sampling: Participants are selected based on ease of access.
Determining Sample Size & Data Collection
- Sample size depends on research goals, desired confidence, margin of error, analysis type, and total population size.
- Use statistical formulas or published tables to determine appropriate sample size.
- Primary data is collected directly by the researcher; secondary data is collected by others.
- Response rate is the percentage of selected individuals who participate in the study.
Key Terms & Definitions
- Sample — A subset of the population chosen for study.
- Population — The entire group of individuals relevant to the research.
- Sampling Frame — The actual list of individuals from which a sample is drawn.
- Subject/Case — An individual participant in the study.
- Response Rate — Percentage of contacted individuals who participate.
Action Items / Next Steps
- Review statistical tables for recommended sample sizes for different research scenarios.
- Prepare to discuss primary vs. secondary data collection methods in the next lecture.