Whats the difference between describing a sample and making an inference about a population parameter?

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Statistical inference involves generalizing from sample data to the wider population from which the sample was drawn. Inferences are made by calculating the probability that, given the size of the sample, chance alone might have accounted for a given observation.

Statistical inference is based on the laws of probability, and allows analysts to infer conclusions about a given population based on results observed through random sampling. Two of the key terms in statistical inference are parameter and statistic:

A parameter is a number describing a population, such as a percentage or proportion.

A statistic is a number which may be computed from the data observed in a random sample without requiring the use of any unknown parameters, such as a sample mean.

orchestra answered 1 year ago

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