SampDist - mean (the standard error of the mean) equals the...

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Chapters 8, 9 and 10: Populations, Samples and Probability, Sampling Distribution of the Mean, The z Test Populations, Samples and Probability Populations and Samples Real populations Random samples Hypothetical populations Random samples vs. Random assignment External validity vs. Internal validity External validity: Findings generalized to population Internal validity: Research free from alternative explanations Probability The addition rule (“or” rule) Mutually exclusive outcomes The multiplication rule (“and” rule) Conditional probabilities Probability and Statistics Rare vs Common events Sampling Distribution of the Mean Definition: Probability distribution of means for all possible random samples of a given size for some population.
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Three key properties: 1) The mean of the sampling distribution of the mean always equals the mean of the population. 2) The standard deviation of the sampling distribution of the
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Unformatted text preview: mean (the standard error of the mean) equals the standard deviation of the population divided by the square root of the sample size. 3) The shape of the sampling distribution of the mean will approximate a normal curve if the sample size is sufficiently large (Central Limit Theorem). The z Test z = (X-bar - μ hyp )/ σ X-bar where X-bar = sample mean μ hyp = Hypothesized population mean and σ X-bar = standard error of the mean (standard deviation of the sampling distribution of the means) Assumptions: 1) The population is normally distributed or the sample size is large enough to satisfy the requirements of the Central Limit Theorem; and 2) The population standard deviation is known Hypothesis Test Summary Research Problem Statistical Hypotheses Decision Rule Calculations Decision Interpretation...
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This note was uploaded on 04/30/2008 for the course PSY 320 taught by Professor Harkins during the Spring '08 term at Northeastern.

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SampDist - mean (the standard error of the mean) equals the...

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