Time and Location: 1:30-3:30pm on Wednesday, December 11, in Eck133

1. Bring a calculator
2. Bring two letter-size formula sheets, two-sided
3. a normal table, a t-table and a chi-square table will be provided in the exam

Coverage: Section 5.1, 5.2, 6.1, 6.2, 6.3, 6.4, 7.1, 7.2, 8.1, 8.2, 9.1, 9.2, 10.1 (see the study guide below for details)

### Study Guide for the Final Exam

#### Section 5.1-5.2

• CLT
• Binomial Formula
• When is Binomial Formula applied?
• CLT for Binomial distribution (np >=10, n(1-p) >=10)
• Skip "Continuity Correction" on p.327
• Skip "Weibull Distribution" on p.330-331

#### Section 6.1

• How to make a confidence interval
• Interpretation of confidence intervals
• Sample size calculation
• When can one NOT use a confidence interval (e.g., not SRS). Read the caution on p.354
• Skip "Bootstrap" on p.355-356

#### Section 6.2

• Hypothesis testing: hypothesis (null, alternative, one-side, two-side), test statistics, p-values, significance level, conclusion
• Interpretation of P-values
• Relationship of a two-sided test and confidence intervals (p.373-375)

#### Section 6.3

• Significance is not importance
• Hypothesis testing cannot tell us if the data is properly collected (e.g., if the experiment or the survey is done properly)
• Beware of searching of significance

#### Section 6.4

• Definition of Type I error, type II error, and the power of a test
• How to increase the power of a test?
• Computation of the power of a test

#### Section 7.1

• t-distribution
• One sample t-test, t-interval (check for skewness and outlier before using t-procedures)
• matched pairs t-test
• Skip p.419-425 (power of the t test, non-Normal populations, ?sign test)
• Skip Exercise 7.45-7.53 on p. 431-432

#### Section 7.2

• Two sample t-test (unequal population SDs)
• pooled two-sample t-test (equal population SDs)
• Check for skewness and outliers before using t-procedures
• Skip the software approximation for the degrees of freedom on p.445

#### Section 8.1

• large-sample C.I. for a single proportion (np >= 15, np(1-p) >= 15)
• Wilson's Plus-Four C.I.for a single proportion (np >= 10, np(1-p) >= 10)
• Test for a single proportion (note the SE is different from the SE for a C.I.)
• Choose a sample size to achieve a specific margin of error

#### Section 8.2

• large-sample C.I. for the difference of two proportions
• Wilson's Plus-Four C.I.for the difference of two proportions
• Test for the difference of two proportions (note we used the pooled SE here)
• Skip Relative Risk on p. 500

#### Section 9.1-9.2

• Chi-square test for two-way tables
• Expected cell counts
• a chi-square test for a 2x2 table is equivalent to a two-sided test for the difference of two proportions
• Skip Meta Analysis on p. 520

#### Section 10.1

• subpopulation (comparison of several populations)
• Assumption of simple linear regression model
• the population regression line v.s.. the sample regression line
• the LS estimate for the intercept and slope are unbiased estimates for the population intercept and slope
• SE for the intercept and slope
• How to reduce the SE of the slope?
• estimate for sigma?
• Use R summary output to find C.I.s and perform t-tests for the intercept and slope
• Prediction intervals v.s. confidence intervals