What is sampling | Probability vs Non Probability sampling | Methods | Types & Technique Explained

Summary

In this video, Aisha explains the concept of sampling in research, focusing on the difference between probability and non-probability sampling methods. Probability sampling ensures random selection, allowing for more accurate statistical inferences, while non-probability sampling is based on convenience and expertise but may introduce bias. Aisha highlights key sampling techniques like simple random, systematic, stratified, and cluster sampling for probability, and convenience, voluntary response, purposive, snowball, and quota sampling for non-probability. The video offers valuable insights for anyone looking to understand how to select representative samples in research.

Takeaways

• 😀 Sampling is the process of selecting a group of individuals to represent a larger population in research.
• 😀 In research, it's often impractical to study every individual in a population, so a sample is chosen.
• 😀 Probability sampling involves random selection, ensuring every individual has a known chance of being chosen.
• 😀 Non-probability sampling involves non-random selection, often based on convenience or judgment, and may introduce bias.
• 😀 Simple random sampling gives each individual an equal chance of being selected from the population.
• 😀 Systematic sampling involves selecting every nth individual from a numbered list of the population.
• 😀 Stratified sampling divides the population into subgroups, ensuring all important groups are represented in the sample.
• 😀 Cluster sampling involves selecting entire subgroups randomly, instead of selecting individuals from each subgroup.
• 😀 Non-probability sampling methods include convenience sampling, voluntary response sampling, purposeful sampling, and snowball sampling.
• 😀 Convenience sampling selects individuals who are easiest to access, but may not be representative of the population.
• 😀 Probability sampling is used for conclusive research, whereas non-probability sampling is more suitable for exploratory research.

Q & A

What is sampling in research?

Sampling in research refers to the process of selecting a group of individuals (a sample) from a larger population to participate in the study, allowing researchers to make inferences about the whole population without collecting data from every individual.

What are the two main types of sampling methods?

The two main types of sampling methods are probability sampling and non-probability sampling. Probability sampling involves random selection, while non-probability sampling involves non-random selection based on criteria like convenience.

What is probability sampling?

Probability sampling is a method in which every member of the target population has a known chance of being included in the sample. It allows for strong statistical inferences about the entire population.

Can you list and explain the types of probability sampling?

The types of probability sampling include: 1) Simple Random Sampling, where each individual has an equal chance of being selected; 2) Systematic Sampling, where individuals are selected at regular intervals; 3) Stratified Sampling, which divides the population into subgroups and ensures proper representation of each subgroup; 4) Cluster Sampling, where entire subgroups are randomly selected instead of individuals.

What is non-probability sampling?

Non-probability sampling is a method where the sample is selected based on non-random criteria. Not every individual has a chance of being included in the sample, making it less representative of the overall population.

What are some common non-probability sampling methods?

Common non-probability sampling methods include: 1) Convenience Sampling, where individuals are selected based on accessibility; 2) Voluntary Response Sampling, where participants choose to join the study; 3) Purposive Sampling, where the researcher uses expertise to select a useful sample; 4) Snowball Sampling, where initial participants recruit additional participants; 5) Quota Sampling, where individuals are selected to meet specific criteria.

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

The main difference is that in probability sampling, every individual has a known and equal chance of being selected, making it random. In non-probability sampling, selection is based on convenience or other criteria, and not everyone has a chance of being included.

Why are samples used in research?

Samples are used in research because they are more practical, cost-effective, and manageable compared to studying an entire population. They also allow researchers to make inferences about the population without needing to collect data from every individual.

What are the advantages of probability sampling over non-probability sampling?

Probability sampling has several advantages, such as generating unbiased results, ensuring a representative sample, and allowing for stronger statistical inferences. It is especially useful when the research is conclusive and seeks to test a hypothesis.

When should non-probability sampling be used in research?

Non-probability sampling should be used when the research is exploratory in nature. It is suitable when randomization is not possible or practical, and the goal is to gather preliminary insights or generate hypotheses rather than make conclusive statistical statements.