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Questions and Answers
In simple random sampling with replacement, every member can be selected more than once.
In simple random sampling with replacement, every member can be selected more than once.
True (A)
Stratified random sampling divides the population into overlapping subgroups called strata.
Stratified random sampling divides the population into overlapping subgroups called strata.
False (B)
A statistical model describes the whole population, while a statistic describes a sample of the population.
A statistical model describes the whole population, while a statistic describes a sample of the population.
True (A)
Systematic sampling selects every nth observation unit from the sampling frame.
Systematic sampling selects every nth observation unit from the sampling frame.
Probability sampling assumes that every element of the target population has an equal chance of being selected in the sample.
Probability sampling assumes that every element of the target population has an equal chance of being selected in the sample.
A parameter is a function of a random sample, while a statistic is a constant that describes the whole population.
A parameter is a function of a random sample, while a statistic is a constant that describes the whole population.
Flashcards
Sampling with replacement
Sampling with replacement
Each member can be chosen multiple times in the sample.
Stratified random sampling
Stratified random sampling
The population is divided into non-overlapping subgroups that share similar characteristics.
Statistical model vs. Statistic
Statistical model vs. Statistic
A statistical model estimates characteristics of the population, while a statistic summarizes data from a sample.
Systematic sampling
Systematic sampling
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Probability sampling
Probability sampling
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Parameter vs. Statistic
Parameter vs. Statistic
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