Yes, under the specified random-sampling model, the sample proportion is unbiased for the population proportion. However, the observed mean of a finite number of estimates need not match the parameter exactly.
Conditions: A specified random-sampling model is used.; The estimator is the sample proportion.; The target parameter is the population proportion.
Yes, under the specified random-sampling model, the sample proportion is unbiased for the population proportion. However, the observed mean of a finite number of estimates need not match the parameter exactly.
Conditions: A specified random-sampling model is used.; The estimator is the sample proportion.; The target parameter is the population proportion.
A dot plot from repeated samples approximates the sampling distribution by showing the empirical frequencies of the statistic's values. It need not include every possible sample and can vary with the number of simulation repetitions.
Conditions: Repeated samples are drawn from the population.; A dot plot is constructed from the resulting statistics.
A dot plot from repeated samples approximates the sampling distribution by showing the empirical frequencies of the statistic's values. It need not include every possible sample and can vary with the number of simulation repetitions.
Conditions: Repeated samples are drawn from the population.; A dot plot is constructed from the resulting statistics.
A sampling distribution records the probabilities of the statistic’s possible values under repeated sampling, given a fixed population, sampling design, and sample size.
Conditions: The population is fixed.; The sampling design is fixed.; The sample size is fixed.
A sampling distribution records the probabilities of the statistic’s possible values under repeated sampling, given a fixed population, sampling design, and sample size.
Conditions: The population is fixed.; The sampling design is fixed.; The sample size is fixed.