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9.1: Sampling Distributions

Vocabulary. Parameter: a number that describes the populationStatistic: a number that is computed from the sample data; usually used as an estimate of the true parameter Sampling distribution: a distribution of the same statistic (for our purposes ) taken from ALL possible samples of the

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9.1: Sampling Distributions

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    1. 9.1: Sampling Distributions

    2. Vocabulary Parameter: a number that describes the population Statistic: a number that is computed from the sample data; usually used as an estimate of the true parameter Sampling distribution: a distribution of the same statistic (for our purposes ) taken from ALL possible samples of the same size from the population.

    3. Variability versus Bias Variability: each sample of the same size taken from the population is likely to vary from other samples of the same size from the same population. Bias: a statistic is biased if the mean of its sampling distribution not equal to the value of the true parameter.

    4. High/low? Variability/bias? Determine if each diagram illustrates high or low variability and bias.

    5. High/low? Variability/bias?

    6. 9.13 An opinion poll asks, Are you afraid to go outside at night within a mile of your home because of crime? Suppose that the proportion of all adults who would say Yes to this question is p = .4. a) Simulate the result with an SRS of twenty adults. Compute . b) Graph the results of 5, 10, 20, and 30 samples. Compute the mean and standard deviation for each sampling distribution. Is each result unbiased? c) Suppose you made a sampling distribution of all possible SRSs of twenty adults from this population. What would the mean and standard deviation be? d) If the population proportion changed to p=.5, what would the mean of the sampling distribution become?

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