Probability Sampling Methods

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Questions and Answers

Which sampling method involves dividing the population into subgroups based on specific characteristics and then randomly selecting from each subgroup?

Simple Random Sampling
Systematic Sampling
Cluster Sampling
Stratified Sampling (correct)

In Systematic Sampling, every member of the population has an equal chance of being selected.

False (B)

Describe the key difference between Simple Random Sampling and Stratified Sampling.

Simple Random Sampling gives every member an equal chance of being selected, while Stratified Sampling ensures representation from specific subgroups by dividing the population into strata and randomly selecting from each stratum.

In _____, the population is divided into clusters, and a random sample of clusters is chosen.

<p>Cluster Sampling</p> Signup and view all the answers

Match the following sampling methods with their descriptions:

<p>Simple Random Sampling = Each member of the population has an equal chance of being selected. Stratified Sampling = The population is divided into subgroups, and a random sample is taken from each subgroup. Systematic Sampling = Every nth element from an ordered list is selected. Cluster Sampling = The population is divided into clusters, and a random sample of clusters is chosen.</p> Signup and view all the answers

Flashcards

Simple Random Sampling

Each member of the population has an equal chance of being selected.

Stratified Sampling

Population is divided into subgroups, and random samples are taken from each subgroup.

Systematic Sampling

Select every nth element from a list for sampling.

Cluster Sampling

Dividing the population into clusters and then randomly selecting some clusters to sample all or some members.

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Probability Sampling

Sampling methods where every member has a known chance of selection.

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Study Notes

Probability Sampling Methods

Simple Random Sampling: Every individual in the population has an identical chance of selection, often using random number generators or a lottery system.
Stratified Sampling: The population is categorized into subgroups (strata) based on shared traits (e.g., age, gender). A random sample is taken from each stratum to ensure representation from all subgroups.
Systematic Sampling: Individuals are selected from an ordered list at fixed intervals. For example, selecting every 10th person on a list.
Cluster Sampling: The population is divided into groups (clusters). A random sample of clusters is chosen, and all members within those selected clusters are included in the study.