Statistics Ch. 7 Probability and Samples/ Distribution of Sample Mean

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law of large numbers

The larger the number of individuals that are randomly drawn from a population, the more representative the resulting group will be of the entire population

central limit theorem

a theorem that states that as the sample size increases, the shape of the distribution of the sample means taken from the population with mean μ and a standard deviation σ/√n

Sampling distribution

is a distribution of statistics obtained by selection all of the possible samples of a specific size from a population

Distribution of sample means

is the collection of sample means for all of the possible random samples of a particular size (n) that can be obtained from a population

sampling error

is the natural discrepancy, or amount of error, between a sample statistic and its corresponding population parameter.

expected value of M

mean of distribution of sample means is equal to the mean of population scores

standard error of M

the standard erro provides a measure of how much distance is expected n average between a sample mean (M) and the population mean


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