Understanding Sampling and Population

What is the difference between a population and a sample?

• A population is the entire group, while a sample is a subset of that group.

• A sample includes the entire population.

• A population is always smaller than a sample.

• A population is a random selection from a sample.

What is simple random sampling?

• A method where only a few members of a population are selected randomly.

• A sampling method where each member of a population has an equal chance of being selected.

• A process that involves selecting members based on their availability at the time of sampling.

• A sampling technique that ensures every member is chosen based on their characteristics.

Describe stratified sampling.

• Stratified sampling is a method where only one stratum is selected for sampling.

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

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

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

What is the main advantage of using cluster sampling?

• Increased efficiency and cost-effectiveness in sampling.

• Simplified data analysis process.

• Higher accuracy in data collection.

• Elimination of sampling bias.

Explain systematic sampling.

• Systematic sampling requires selecting individuals based on their characteristics.

• Systematic sampling involves choosing individuals randomly without a fixed interval.

• Systematic sampling is the same as stratified sampling, which divides the population into subgroups.

• Systematic sampling involves selecting a random starting point and then choosing every nth individual from a population.

What is non-probability sampling?

• Non-probability sampling is a technique that guarantees equal representation of all groups.

• Non-probability sampling is a method where samples are selected based on subjective criteria rather than random selection.

• Non-probability sampling is a method that uses random selection to choose samples.

• Non-probability sampling involves selecting samples based on statistical formulas.

Give an example of convenience sampling.

• Collecting data from a government database.

• Interviewing random people on the street.

• Surveying customers at a local coffee shop.

• Conducting a nationwide survey via email.

What is quota sampling?

• Quota sampling is a method that randomly selects participants without considering subgroups.

• Quota sampling is a technique that does not require any predetermined criteria for participant selection.

• Quota sampling involves surveying only one subgroup to gather data.

• Quota sampling is a method of sampling that involves selecting a predetermined number of participants from various subgroups to ensure representation.

How does snowball sampling work?

• Snowball sampling requires participants to fill out a survey before being included.

• Snowball sampling involves random selection of participants from a population.

• Snowball sampling is a method where researchers select participants based on their qualifications.

• Snowball sampling works by having current participants refer new participants, expanding the sample size through social networks.

What is the purpose of sampling in research?

• To ensure every individual is surveyed in detail.

• The purpose of sampling in research is to make inferences about a population based on a subset.

• To collect data from the entire population directly.

• To eliminate the need for statistical analysis.