Parameter: A number that describes the population. Statistic: A number that can be computed from the sample data without making use of any unknown parameters. Remember s and p: statistics come from samples, and parameters come from populations. μ: mean of a population : mean of a sample The sample mean from a sample or an experiment is an estimate of the mean μ of the underlying population. Probability model: A mathematical description of a random phenomenon consisting of two parts: a sample space S and a way of assigning probabilities to events. If we keep on taking larger and larger samples, the statistic is guaranteed to get closer and closer to the parameter μ. If we can afford to keep on measuring more subjects, eventually we will estimate the mean odor threshold of all adults very accurately. This remarkable fact is called the law of large numbers. It is remarkable because it holds for any population. Law of large numbers: Draw observations at random from any population with finite mean μ. As
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