Exam_2_Review

# Exam_2_Review - Degrees of freedom – Why is one lost t...

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11/9/10 1 Exam 2 Chapters 7-11 7: Sampling Distribution of the Mean Sampling distribution of the mean – Mean – Standard Error – Sample size and standard error – Central Limit Theorem z -score formula for a sample mean solve for z -score solve for sample mean 8a: Hypothesis Testing Probability of an outcome z test for a single population mean H 0 and H 1 Critical z scores Level of significance ( alpha ) Two-tailed vs. One-tailed – sensitivity 8b: More Hypothesis Testing Significance 4 possible outcomes – Type I and Type II error – Alpha; Beta; Power Effect and distributions – when H 0 is false – when H 0 is true calculating effect size More about z tests — assumptions

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11/9/10 2 9: t Test for a Single Sample z vs. t test – Known vs. unknown population standard deviation H 0 and H 1 t ratio Sample standard deviation – Estimated population standard deviation Estimated standard error 9: t Test for a Single Sample
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Unformatted text preview: Degrees of freedom – Why is one lost? t Distributions – Finding critical scores – A family of distributions Degrees of freedom – Relationship between t and z Assumptions Measures of effect size 10: t Test for Two Independent Samples Independent samples H and H 1 t ratio – Degrees of freedom Estimated Standard Error Pooled variance Measures of effect size Assumptions 11: t Test for Two Dependent Samples Dependent Samples Difference scores H and H 1 Estimated standard error – Compared to estimated standard error for independent samples – Matching and standard error t ratio – degrees of freedom 11/9/10 3 Matching and sensitivity – Estimated standard error – Degrees of freedom Repeated measures – Counterbalancing Assumptions Measures of effect size 11: t Test for Two Dependent Samples...
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Exam_2_Review - Degrees of freedom – Why is one lost t...

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