Sampling Methods in Research

This video tutorial covers various sampling methods, including probability and non-probability sampling. It explains the reasons for sampling, the importance of a sampling frame, and potential errors. The tutorial details different types of sampling methods such as simple random, systematic, stratified, cluster, multistage, and matched random sampling. It also discusses non-probability methods like convenience, quota, and purposive sampling. The video concludes with an overview of judgement and panel sampling, emphasizing the importance of selecting a representative sample.

What is the primary objective of sampling in research?

• To include every individual in the population

• To avoid any form of bias

• To save time and resources

• To ensure 100% accuracy

Why is a sampling frame important in research?

• It ensures all potential respondents are included

• It eliminates the need for statistical analysis

• It guarantees a high response rate

• It provides a list of all possible samples

Which factor does NOT influence a sample's representativeness?

• Researcher's personal opinion

• Response rate

• Sampling procedure

• Sample size

What distinguishes probability sampling from non-probability sampling?

• Probability sampling includes all population members

• Non-probability sampling is more cost-effective

• Non-probability sampling is always more accurate

• Probability sampling gives each unit a known chance of selection

In simple random sampling, what is a key characteristic?

• It is the same as systematic sampling

• It is only used for large populations

• Each unit has an equal chance of being selected

• It requires a complex sampling frame

What is a disadvantage of systematic sampling?

• It requires a large sample size

• It is not suitable for homogeneous populations

• It may introduce bias if there is a hidden pattern

• It is difficult to implement

How does stratified sampling differ from cluster sampling?

• Stratified sampling ensures all strata are represented

• Cluster sampling requires a smaller sample size

• Cluster sampling is more accurate

• Stratified sampling uses non-overlapping subsets

What is a key feature of multistage sampling?

• It involves only one stage of sampling

• It is used when a complete list of the population is available

• It combines several sampling methods

• It is the same as cluster sampling

What is the main advantage of convenience sampling?

• It eliminates all forms of bias

• It is highly representative

• It is easy and quick to implement

• It requires a detailed sampling frame

What is a wave in panel sampling?

• A type of non-probability sampling

• A period of data collection

• A single data collection point

• A method of selecting participants