ExamIII_Review_Lst.pdf
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Exam III Review, Stat 4813, Spring 2013 Chapter 6. • Distribution of X, X ∼ N (μ, σ 2 /n) • Calculations: E( X ),V ( X ),P ( X ≤ 17),P ( X>c)= .90 Chapters 7 and 8. •When does one use the σ know, large sample, small sample cases in confidnence intervals and tests of hypotheses? • In the case of σ known and assuming normality, compute the Type I error probability α for a specified rejection region and compute the Type II error probability β (μ ′ ) for a specific alternative μ ′ . •Define and compute the p-value of a test. •How does the p-value enter into the decision to reject or not reject the null hypothesis? •Carry out a test of hypothesis and interpret the results. Chapter 9. •Confidence intervals and tests of hypotheses for two sample mean difference. •Paired sample mean difference. Chapter 12. •General questions about the simple linear regression model. •Given the data summaries • n, ∑ x i , ∑ y i , ∑ x 2 i , ∑ y 2 i , ∑ x i y i •Calculate the coefficients, residual variance, and R 2 . (Table of formulae from Chapter 12 will be provided.) •Find CI for the slope. •Test hypothesis about slope. • Computer point estimate of the average (mean) of y for a specific value x ∗ . • Interpret a given a Confidence Interval for the average (mean) of y for a specific value x ∗ . • Interpret a given a Prediction Interval for the single value of y for a specific value x ∗ . • Given the print out and the graphs for a simple linear regression problem, extract various quantities that are needed for a standard analysis. Tables for the standard normal and the t distributions will be supplied. Formulae for the simple linear regression analysis will be supplied. Calculators are necessary. 1
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Transcript of ExamIII_Review_Lst.pdf
Exam III Review, Stat 4813, Spring 2013
Chapter 6.
• Distribution of X, X ∼ N(µ, σ2/n)• Calculations: E(X), V (X), P (X ≤ 17), P (X > c) = .90
Chapters 7 and 8.
•When does one use the σ know, large sample, small sample cases in confidnenceintervals and tests of hypotheses?
• In the case of σ known and assuming normality, compute the Type I errorprobability α for a specified rejection region and compute the Type II error probabilityβ(µ′) for a specific alternative µ′.
•Define and compute the p-value of a test.•How does the p-value enter into the decision to reject or not reject the null
hypothesis?•Carry out a test of hypothesis and interpret the results.
Chapter 9.
•Confidence intervals and tests of hypotheses for two sample mean difference.•Paired sample mean difference.
Chapter 12.
•General questions about the simple linear regression model.•Given the data summaries• n,
∑xi,
∑yi,
∑x2
i,
∑y2i,
∑xiyi
•Calculate the coefficients, residual variance, and R2.(Table of formulae from Chapter 12 will be provided.)•Find CI for the slope.•Test hypothesis about slope.• Computer point estimate of the average (mean) of y for a specific value x∗.• Interpret a given a Confidence Interval for the average (mean) of y for a specific
value x∗.• Interpret a given a Prediction Interval for the single value of y for a specific
value x∗.• Given the print out and the graphs for a simple linear regression problem, extract
various quantities that are needed for a standard analysis.
Tables for the standard normal and the t distributions will be supplied.Formulae for the simple linear regression analysis will be supplied.Calculators are necessary.
1
