Statistics Sampling Methods Chapter

Key Definitions

• Population: Complete set of subjects (people or objects) that share common characteristics being studied.
• Sample: Subgroup of the population selected for study to infer findings about the entire group.

Types of Population

• Target Population: Entire group the researcher wishes to generalize findings to; can include specific criteria (e.g., all institutionalized individuals with psychiatric issues).
• Accessible Population: Group actually available for study; may differ from the target population (e.g., pregnant women in a specific clinic setting).

Importance of Sampling

• Essential to choose a representative sample to answer research questions accurately.
• Sample size must be appropriate to ensure research validity.

Advantages of Sampling

• Cost-effective approach.
• Requires less manpower than studying entire populations.
• Information gathered more quickly.
• Ability to obtain comprehensive data.
• Can yield greater accuracy, sometimes providing better estimates than complete surveys.

Types of Sampling Procedures

• Probability Sampling: Random selection process ensuring every population member has an equal chance of being selected.
• Non-Probability Sampling: Selection based on non-random criteria.

Probability Sampling Methods

• Simple Random Sampling (SRS): Every member has an equal chance; achieved via random selection methods such as shuffling cards or using random number generators.
• Systematic Random Sampling: Selection process involves determining a sampling proportion (sample size/population size) and then selecting members at regular intervals.
• Stratified Random Sampling: Population divided into homogeneous strata; samples are drawn from each stratum ensuring equal representation.
• Multistage Random Sampling: Involves selecting samples at various stages (e.g., regions to villages to schools).
• Cluster Random Sampling: Useful when populations are geographically spread; samples drawn from randomly selected clusters (e.g., schools in a district).

Random Sampling Techniques

• For Systematic Random Sampling, after preparing the sampling frame, determine the starting point randomly, then sample at calculated intervals.
• Stratified Sampling ensures all key groups (strata) within the population are represented proportionally.

Conclusion

• Selecting appropriate sampling methods is crucial for the representativeness and validity of research findings.
• Understanding the structure of the population aids in effective sampling strategies.