Sampling Methods and Validity Concepts

The video tutorial explains the concept of sampling in research, highlighting its importance in making inferences about a population without conducting a full census. It covers defining target, source, and study populations, and discusses internal and external validity. The tutorial differentiates between probability and non-probability sampling, providing examples of each. It also details random sampling methods, including simple, systematic, and stratified approaches. Finally, it offers guidance on choosing an appropriate sampling plan based on available resources and research objectives.

Why is sampling often preferred over conducting a census?

• It eliminates the need for data analysis.

• It is more accurate.

• It is less costly and time-consuming.

• It includes the entire population.

What is the first step in effective sampling?

• Choosing a sampling method.

• Defining the population of interest.

• Analyzing results.

• Collecting data.

What does internal validity refer to?

• The cost-effectiveness of the study.

• The accuracy of the data collected.

• How well study results relate to the source population.

• The ability to generalize results to the target population.

What is the main difference between probability and non-probability sampling?

• Probability sampling is more expensive.

• Probability sampling involves random selection.

• Non-probability sampling is more accurate.

• Non-probability sampling includes the entire population.

Which of the following is an example of non-probability sampling?

• Stratified random sampling.

• Convenience sampling.

• Simple random sampling.

• Systematic random sampling.

Why might non-probability sampling have poor validity?

• It includes the entire population.

• It requires complex analysis.

• It is too expensive.

• Selected members may differ from those not selected.

What is a key advantage of probability sampling?

• It is less time-consuming.

• It ensures a representative sample.

• It requires fewer resources.

• It is easier to conduct.

In systematic random sampling, how are members chosen?

• From a single stratum.

• Based on specific characteristics.

• At regular intervals after a random start.

• Randomly from the entire population.

What is the purpose of stratified random sampling?

• To ensure equal representation of subgroups.

• To reduce the cost of sampling.

• To focus on a single characteristic.

• To simplify the sampling process.

What should be considered when choosing a sampling method?

• All of the above.

• The impact on validity.

• The resources available.

• The size of the population.