Introduction
[1] Sept 5
 course description and evaluation
 introduction to statistical analysis in medicine
 math background

 Colton
 Moore and McCabe
 Armitage and Berry

Data Summaries and Descriptive Statistics
[2] Sept 7  Sept 12
 types of data
 histograms
 stemplots
 boxplots
 means
 medians
 variance
 relocating/rescaling

 Colton
 Chapter 2 pp 1144
 Boxplots and stemplots not covered.
 Moore and McCabe
 Chapter 1 pp 158
 Chapter 2 pp 106107
 Armitage and Berry
 Chapter 1 pp 440
 Boxplots, stemplots not covered

Probability and Probability Distributions
[3] Sept 14  Sept 21
 laws of probability
 discrete and continuous random variables
 expectation and variance of r.v.'s
 diagnostic tests and conditional probabilities
 Bayes Theorem
 Normal distribution
 area under Normal curve
 binomial distribution
 Normal approximation to the binomial
 Poisson distribution

 Colton
 Moore and McCabe
 Chapter 1 pp 6479
 Chapter 3 pp 267275
 Chapter 4 pp 287357
 Chapter 5 pp 374390
 Diagnostic tests not covered
 Armitage and Berry
 Chapter 2 pp 4177
 Chapter 16 pp 522525

Inference Concerning Means
[4] Sept 26  Oct 19
 random sampling
 hypothesis testing for means
 type I and type II errors
 pvalues
 confidence intervals for means
 t distribution
 paired and unpaired samples
 Bayesian inference
 sample size calculations and power

 Colton
 Chapter 4 pp 99146
 Bayes not covered
 Moore and McCabe
 Chapter 5 pp 397405
 Chapter 6 pp 432493
 Chapter 7 pp 502555
 Bayes not covered
 Armitage and Berry
 Chapter 3 pp 7884
 Chapter 4 pp 93114, 146149

Midterm Exam
Tuesday October 24, 2000, 9:00 am  11:00 am
 Room N2/D2, Stewart Biology Building

Inference concerning proportions and counts
[5] Oct 26  Nov 9
 hypothesis testing for proportions
 sample size calculations and power
 paired and unpaired samples
 chi_2test to compare 2 or more proportions
 Fishers exact test
 Bayesian inference
 MantelHaenzel to combine 2 x 2 tables
 relative risk and odds ratios
 inference for count data

 Colton
 Chapter 5 pp 151183
 Bayes, Mantel Haenzel, relative risk and odds ratio not covered
 Moore and McCabe
 Chapter 8 pp 584609
 Fishers exact test, Bayes, MantelHaenzel, relative risk, odds ratios and counts not covered
 Armitage and Berry
 Chapter 3 pp 8485
 Chapter 4 pp 118152
 Chapter 16 pp 508519
 Bayes not covered

Nonparametric Statistics
[6] Nov 14  Nov 16
 sign test
 Rank sum test
 Wilcoxon signed rank test
 CI for median

 Colton
 Chapter 7 pp 219226
 Sign test and CI not covered
 Moore and McCabe
 Chapter 14 (0n CDROM only)
 Armitage and Berry
 Chapter 13 pp 448460
 CI not covered

Regression and Correlation
[7] Nov 21  Dec 5
 difference between regression and correlation
 scatter plots
 linear regression
 least squares method
 estimation of parameters in regression
 Bayesian inference in regression
 basic design in regression
 other types of regression
 Pearson's correlation
 Spearman's correlation

 Colton
 Chapter 6 pp 189214
 Bayes not covered
 Moore and McCabe
 Chapter 2 pp 126168
 Chapter 10 pp 660694
 Bayes not covered
 Armitage and Berry
 Chapter 5 pp 154171
 Bayes not covered

Final Exam
Thursday December 7, 2000, 9:00 am  12:00 pm
 Room 129, Education Building
