Summary of Topics Covered in STAT 535
- Probability (needed to understand the statistical methods)
- random variables & distributions (incl. commonly used normal and
binomial distributions)
- moments (mean, variance, skewness, kurtosis)
- independence
- law of large numbers & central limit theorem
- Basics of Statistics
- point estimators, confidence intervals, and test statistics
- standard errors & sampling distributions
- size, power, & p-values
- Inferences from One or Two Samples
- Student's t test and confidence interval for one sample,
paired data, and two independent samples
- effect of nonnormality and heteroscedasticity
- diagnostic methods for checking assumptions
- Welch's procedures for handling unequal variances
- nonparametric methods (sign test, Wilcoxon signed-rank test,
Wilcoxon rank sum test (Mann-Whitney test))
- Inferences from Three or More Samples
- one-way ANOVA F test and multiple comparison procedures
- methods for dealing with unequal variances
- nonparametric methods
- Considerations for Experimental Designs and Modeling
- observational units & the roles of randomization, replication, and
blocking
- controls & blinding
- confounding & spurious associations
- extraneous variables & modeling
- Two-way ANOVA and Methods for Other Designs
- crossed and nested (hierarchical) designs
- interactions
- analysis of covariance
- Correlation and Regression
- correlation and measures of association
- simple linear regression
- multiple regression modeling (polynomial regression, interactions)
- checking assumptions and making transformations
- Categorical Data Analysis
- Pearson's goodness-of-fit tests
- contingency tables & tests for lack of independence
- brief coverage of logistic regreession