Sampling Concepts and Methods

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

• Non-probability sampling involves random selection of participants.

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

• The main difference is that probability sampling uses random selection, while non-probability sampling does not.

• Probability sampling is used only in qualitative research.

Define simple random sampling and provide an example.

• Picking 10 students based on their grades without randomization.

• Selecting 10 students from a class of 50 by choosing the first 10 on the list.

• Choosing every 10th student from a class of 100 without random selection.

• An example of simple random sampling is selecting 10 students from a class of 100 by assigning each student a number from 1 to 100 and using a random number generator to pick 10 unique numbers.

What is stratified sampling and when is it used?

• Stratified sampling is used only for small populations with no subgroups.

• Stratified sampling is a method to randomly select individuals from a population.

• Stratified sampling is a sampling method used to ensure representation of specific subgroups within a population.

• Stratified sampling involves selecting every individual from the population without any criteria.

Explain the concept of systematic sampling.

• Systematic sampling involves random selection of samples from a population.

• Systematic sampling is a method of choosing samples based on personal preference.

• Systematic sampling is a method of selecting samples at regular intervals from a population.

• Systematic sampling requires the use of complex statistical formulas to select samples.

What are the advantages of using cluster sampling?

• High accuracy in small populations

• Increased complexity in data collection

• Advantages of cluster sampling include cost-effectiveness, time efficiency, and potential for improved representativeness.

• Requires a larger sample size than simple random sampling

Describe convenience sampling and its potential biases.

• It is a method that randomly selects participants from a large database.

• Convenience sampling ensures a diverse representation of the population.

• Convenience sampling is a technique that eliminates all biases in research.

• Convenience sampling is a method of selecting samples based on ease of access, which can introduce biases due to lack of representativeness.

What is the purpose of using a sampling frame?

• To analyze the results of the sample after selection.

• To ensure the sample is representative of the entire population.

• To collect data from the sample directly.

• To provide a list or database of elements from which a sample can be selected.

How does quota sampling differ from stratified sampling?

• Stratified sampling is less structured than quota sampling.

• Quota sampling requires equal representation from all groups; stratified sampling does not.

• Quota sampling is non-random; stratified sampling is random.

• Quota sampling uses random selection; stratified sampling does not.

What is the role of sample size in statistical analysis?

• Sample size is crucial for accuracy, reliability, and validity in statistical analysis.

• Sample size is only important for qualitative research.

• Larger sample sizes always lead to incorrect conclusions.

• Sample size has no impact on statistical results.

Explain the concept of sampling error.

• Sampling error is the same as measurement error.

• Sampling error occurs only in large samples.

• Sampling error is the total number of samples taken from a population.

• Sampling error is the difference between a sample statistic and the actual population parameter due to the sample not perfectly representing the population.