Exploring Sample Design Concepts

What is the primary purpose of sample design?

• To collect data from a small group only.

• To analyze past data trends without sampling.

• To ensure accurate representation of a population for valid data collection.

• To create a biased view of the population.

Explain the difference between probability and non-probability sampling.

• Non-probability sampling guarantees equal chances of selection for all participants.

• Probability sampling provides a method for statistical inference, while non-probability sampling does not ensure equal selection chances and may introduce bias.

• Probability sampling is always more expensive than non-probability sampling.

• Probability sampling is used only in qualitative research.

What factors should be considered when determining sample size?

• Number of researchers and funding amount

• Sample color, temperature, and humidity

• Time of day, location, and weather conditions

• Population size, margin of error, confidence level, variability, and study design.

Describe the concept of stratified sampling.

• Stratified sampling is a technique where the population is divided into strata, and samples are drawn from each stratum to ensure representation.

• Stratified sampling requires that all individuals in the population are sampled equally.

• Stratified sampling is a method where only one stratum is sampled to represent the whole population.

• Stratified sampling involves selecting a single sample from the entire population.

What is the role of a sampling frame in sample design?

• The role of a sampling frame in sample design is to provide a complete and accurate list of the population from which a sample can be drawn.

• It helps in determining the sample size needed for research.

• It is used to analyze the data collected from the sample.

• It provides a method for randomizing the selection process.

How does convenience sampling differ from random sampling?

• Convenience sampling is always random and unbiased.

• Convenience sampling is non-random and biased, whereas random sampling is systematic and unbiased.

• Random sampling is based on convenience and accessibility.

• Both sampling methods yield the same results regardless of the approach.

What are the potential biases associated with sample design?

• Analysis bias

• Data entry bias

• Potential biases associated with sample design include selection bias, non-response bias, measurement bias, convenience sampling bias, and sampling frame errors.

• Response bias

Why is it important to define the target population in sample design?

• To ensure the sample is as diverse as possible without any criteria.

• It is important to define the target population to ensure accurate representation and valid results.

• To focus only on a specific demographic regardless of relevance.

• To limit the sample size and reduce costs.