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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?
Which sampling method involves dividing the population into subgroups based on specific characteristics and then randomly selecting from each subgroup?
In Systematic Sampling, every member of the population has an equal chance of being selected.
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.
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.
In _____, the population is divided into clusters, and a random sample of clusters is chosen.
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Match the following sampling methods with their descriptions:
Match the following sampling methods with their descriptions:
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Study Notes
Probability Sampling Methods
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Simple Random Sampling: Every individual in the population has an identical chance of selection, often using random number generators or a lottery system.
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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.
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Systematic Sampling: Individuals are selected from an ordered list at fixed intervals. For example, selecting every 10th person on a list.
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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.
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Description
This quiz covers various probability sampling methods including Simple Random Sampling, Stratified Sampling, Systematic Sampling, and Cluster Sampling. Each method is explained in detail to understand its application and importance in statistics.