Population vs Sample / Sampling Methods

Front

What is the difference between a population and a sample?

Back

A population is the entire group of individuals or objects being studied, while a sample is a subset of the population selected for analysis.

Front

Define 'Statistics' in the context of data analysis.

Back

Statistics refers to the numerical data derived from a sample, used to estimate or infer characteristics of the population.

Front

What is 'Simple Random Sampling'?

Back

Simple Random Sampling is a sampling method where every individual in the population has an equal chance of being selected.

Front

Explain 'Cluster Sampling'.

Back

Cluster Sampling involves dividing the population into groups (clusters) and randomly selecting entire clusters for analysis.

Front

What is 'Systematic Sampling'?

Back

Systematic Sampling is a method where you select every nth individual from a list of the population.

Front

Define 'Stratified Sampling'.

Back

Stratified Sampling involves dividing the population into subgroups (strata) and randomly sampling from each stratum.

Front

What is a 'Parameter' in statistics?

Back

A Parameter is a numerical value that summarizes a characteristic of a population.

Front

What is a 'Random Sample'?

Back

A Random Sample is a subset of individuals chosen from a larger set, where each individual has an equal chance of being selected.

Front

What does 'Convenience Sampling' mean?

Back

Convenience Sampling is a non-random sampling method where individuals are selected based on their easy availability.

Front

What is the purpose of sampling in statistics?

Back

The purpose of sampling is to gather data from a subset of a population to make inferences about the entire population.