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Confidence Intervals

# Confidence Intervals - Confidence Intervals Known =...

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Confidence Intervals

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Known = population in general Unknown = population your sample is from Known Unknown
Hypotheses Research: Your sample is different from the known population Null: Your sample is not different from the known population

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Known Population Population 1 (X 1 ’s) μ 1 and σ 2 1 and σ 1 Population 2 (X 2 ’s) μ 2 and σ 2 2 and σ 2 Unknown Population Distribution of Sample Means (M 1 ’s) M m1 SE m1 Distribution of Sample Means (M 2 ’s) M m2 SE m2 Sample (a few X 2 ’s) M 2 and s 2 2 and s 2 Sample (a few X 1 ’s) M 1 and s 2 1 and s 1 Since we use samples, we need sampling distributions (distribution of sample means).
z cut-offs (two-tailed, alpha = .05) SCORE -4 -2 0 2 4 0.0 0.1 0.2 0.3 0.4 +1.96 -1.96 This is the sampling distribution of the known population. We compare our sample mean to this distribution of means. Reject the null if beyond +1.96/-1.96.

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Standard Error of the Mean N N M σ or 2 = To find the SD of the sampling distribution of means, all you need to know is the standard deviation of scores in the population , and your sample size.
Confidence Interval (CI) The sample mean is an estimate of the unknown population mean. Confidence Interval: The interval in which you estimate the true (unknown) population mean lies.

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95% confidence interval SCORE -4 -2 0 2 4 0.0 0.1 0.2 0.3 0.4 +1.96 -1.96 This is the sampling distribution of the
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Confidence Intervals - Confidence Intervals Known =...

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