Statistics 302, Sections 505-506, H.J. Newton
Studying for the Final Exam
Tuesday May 5, 1997, 10:30-12:30, Blocker 165
Structure of the Exam
- 5 multiple choice similar to those on first exam.
- 5 multiple choice similar to those on second exam.
- 10 multiple choice covering material since second exam.
- A rank-sum test problem.
- One multi-part regression problem based on Stataquest output.
- One multi-part 1-way ANOVA problem based on Stataquest output.
- A Tukey-Kramer multiple comparison problem.
- Any needed formula will be supplied except the sample mean and variance
and interquartile range.
- Make sure you can use the tables 2, 3, 4, 6, and 7 in the back of the
- Make sure you can plug numbers into formulas and get the right answer.
Outline of Material Since Second Exam
- Chapter 10
- Mann-Whitney Rank Sum Test
- Null hypothesis
- Ranking data
- Using Table VI (pg 611)
- Chapter 11
- Simple Linear Regression
- Probabilistic and deterministic models
- Independent and dependent variables
- Understanding assumptions about populations of y's for fixed x.
- Linearity of means
- Normality of populations
- Constancy of variances
- Independence of populations
- Checking assumptions
- Interpreting graphs of residuals
- Interpreting slope and intercept
- Understanding residuals
- Interpreting R^2
- Testing hypotheses about a slope
- Prediction intervals and confidence intervals
- Inferences about correlation coefficient (rho)
- The bivariate normal distribution
- Performing a test that rho is zero
- Chapter 13
- A completely randomized design one factor (1-way) design
- A randomized block design
- A completely randomized two factor (2-way) design
- Sources of variation for 1-way, randomized block, and 2-way
- The assumptions for ANOVA
- All poulations are normally distributed with the same variance
- Between and within sample variation
- The null and alternative hypotheses
- The Tukey-Kramer multiple comparison procedure for 1-way ANOVA
- Properties of the F curves
- Always positive, average value 1, curve gets more symmetric as
degrees of freedom increase