Sampling Methods and Bias Analysis

To gather data quickly.

To focus on a specific subgroup.

To ensure every individual has an equal chance of being selected.

To select individuals based on convenience.

Asking for volunteers to participate.

Dividing the population into groups and sampling each group.

Selecting every nth individual from a list.

Putting all names in a hat and drawing randomly.

Equal parts.

Strata or layers.

Random intervals.

Convenient groups.

Selecting individuals based on their availability.

Choosing every nth individual from a list.

Dividing the population into strata.

Asking for volunteers.

It introduces systematic errors.

It is always random.

It is the most reliable method.

It accurately represents the population.

It is time-consuming.

It requires complex calculations.

It does not represent the entire population.

It is too expensive.

It is based on systematic intervals.

It includes only those who are easy to reach.

It relies on random selection.

It only includes those who choose to participate.

Convenience sampling

Systematic sampling

Stratified random sampling

Simple random sampling

Biased sampling is always preferred.

Random sampling is ideal but not always feasible.

Biased sampling is more accurate.

Random sampling is always easy to implement.