﻿ Biostatistics Course

# Biostatistics Course

Updated Tuesday July 29, 2008 12:00 AM
| dj1480
•  Stat formulas in ExcelAll the basic formulas and definition, with Excel calculations and Stat hints
•  STATA reference sheetCommon commands defined

• ### Homework

•  Homework 2 - CrowleyDescriptive statistics, false positive/negative, SD
•  Homework 3- CrowleyConfidence intervals, power, hypothesis testing
•  Homework 3B - Crowleyt-tests
•  Homework 4 - CrowleyConfidence intervals
•  Homework 5 - CrowleyContingency tables, relative risk
•  Homework 6 - CrowleyAnalysis of variance
•  Extra Credit Homework - CrowleyRegression
• ### Lecture 1 - Intro & Descriptive Statistics

•  Lecture 1 - Handouts not online:Samples: tables, graphs, STATA output, box plots, frequency charts
• ### Lecture 2 - Normal Distribution & Standardization

•  Lecture 2 slidesSamples, means, central tendencies, variance, SD, normal distribution, standard distribution
•  Handouts not online- ACTG A5087: sample of actual analysis
• ### Lecture 3 - Screening Tests & Probabilities

•  Lecture 3 slidesScreening tests, probabilities, sensitivity and specificity, ROC curves
•  Lect 2 - handouts not on-line- Answering Marilyn's Question (Positive Predictive Value) - Screening test for TB (prior probabilities, posterior probability) - ROC Curve (the trade-off between sensitivity and specificity)
• ### Lecture 4 - The Central Limit Theorem

•  Lecture 4 slidesCentral limit theorem, hypothesis testing, p-values, alpha/beta errors
•  Central Limit Theorem - handoutThe mathematics of the CLT, explained
•  CLT Example - Article about HIV2 pages of text, 4 pages of data. Y!
•  Central Limit - HIV Example 2More data, smaller print
• ### Lecture 5 - Hypothesis Testing & t-tests

•  Lecture 5 topics- Review of hypothesis testing - Z-test - t-tests, t-distribution - degrees of freedom - one-sample population mean - two independent samples - dependent (paired) samples
•  Lecture 5 materials not online- The slides (not found) - Summary definition of Z-test, t-test; assumptions and conditions - Example: Level of Benzene in a Cigar
• ### Lecture 6 - Sample Size

•  Lecture 6 slidesSample size and power; steps to determine sample size; impact of variability (SD); calculations; adjustments
• ### Lecture 7 - Mid-term review

•  Mid Term Reviewnote: powerpoint slides
•  Sample Mid-term examFrom Spring of 2004
• ### Lecture 8 - Confidence Intervals

•  Lecture 8 slidesConfidence intervals, inference vs. hypothesis testing
•  Review of Confidence IntervalsMore math
• ### Lecture 9 - Proportions

•  Lecture 9 slides - part IProportions, counts, binary data, inference on proportions
•  Lecture 9 slides - part IIEstimation of proportion, hypothesis testing on proportions
•  Lecture 9 slides - part IIIWorking through an example of counts and proportions
• ### Lecture. 10 - Contingency Tables

•  Lecture 10 slidesCategorical data, chi-square tests, exact tests, Odds Ratio, interactions, Mantel-Haenszel methods
•  Lecture 10 handouts not on-line- Additional slides re Contingency tables - Chi-square examples - OR examples, 3x2x2 tables - Racial profiling example
• ### Lecture. 11 - Analysis of Variance (ANOVA)

•  Lecture 11 slidesANOVA
•  Material not on-lineSlides part II - ANOVA: hypothesis testing for 3 or more means; bonferroni corrections
• ### Lecture. 12 - Correlation & Linear Regression

•  Lecture 12 slides - part ISimple linear regression; pearson correlation coefficient; Spearman rank correlation coefficient; least-squares method; residuals; CI of regressions; Multiple regression
•  Lecture 12 slides - part IICorrelation: hypothesis testing; degrees of freedom; analysis of variance; the F test of linear association; regression as an alternative to correlation
•  Example: Growth vs DoseSimple correlation
• ### Lecture. 13 - Clinical Trials

•  Lecture 13 slidesClinical Trials: the process for testing a new drug or device; statistical issues: randomization, stratification, blinding, designs, non-inferiority study
• ### Lecture. 14 - Final Review

•  Final Review slidesConfidence intervals, Proportions, Contingency tables, ANOVA, Correlation, Regression, Clinical trials