This page includes the asynchronous lecture videos, PDF slides, and other materials for Biostatistical Methods I (BIOS 6611) for Fall 2020/2021/2022. Note that later semesters may use different materials and cover different topics. The material is broadly broken down by theme with links provided to download materials or view the videos. A brief overview of the material covered in a given lecture can be viewed by hovering over or clicking the given “Lecture Topic”.
Probability and Distributions
The first theme in BIOS 6611 discusses core concepts in statistics (e.g., simulation studies, estimators, estimation) and both discrete and continuous probability distributions.
Hypothesis Testing, Power, Sample Size
The second theme of BIOS 6611 introduces the framework for hypothesis testing based on null hypothesis significance testing (NHST). We then discuss the concept of power calculations and work through practical examples by hand and using R to estimate power, sample size, or a detectable difference.
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Lecture Topic
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Slides
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Video Link
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Fisher’s p-value
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PDF
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YouTube
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The Neyman-Pearson Tradeoffs
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PDF
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YouTube
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Null Hypothesis Significance Testing (Fisher-Neyman-Pearson Hybrid)
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PDF
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YouTube
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Statistical Power and Derivations for a Two-Sided, One-Sample Z-test
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PDF
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YouTube
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Power Calculation Examples in R
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PDF
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YouTube
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Conditional Probability, Effect Measures, Inference for 2x2 Tables
Our third theme in BIOS 6611 explores conditional probability and its application for diagnostic testing as well as studies with 2x2 tables and inference based on risk differences, risk ratios, or odds ratios.
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Lecture Topic
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Slides
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Video Link
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Diagnostic Testing: Sensitivity and Specificity
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PDF
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YouTube
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Diagnostic Testing: Predictive Values and Odds
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PDF
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YouTube
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Diagnostic Testing: ROC Curves
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PDF
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YouTube
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Observational Study Designs
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PDF
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YouTube
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2x2 Tables Measures of Effect: RD, RR, OR
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PDF
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YouTube
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2x2 Tables and Tests of Association
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PDF
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YouTube
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Bootstrap Sampling and Nonparametric Methods
The fourth theme of BIOS 6611 explores bootstrap resampling, permutation testing, and other nonparametric methods for hypothesis testing.
Simple Linear Regression
In our fifth theme of BIOS 6611 we introduce, derive, and apply methods for linear regression with a single predictor for a continuous outcome. The lectures include a mix of applied and theoretical content.
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Lecture Topic
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Slides
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Video Link
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Simple Linear Regression (SLR) Introduction
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PDF
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YouTube
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SLR: Find the “Best” Fit and Summary Formulas
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PDF
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YouTube
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SLR: Simple Application and Hypothesis Testing
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PDF
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YouTube
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SLR: Quality of Fit, F-test, and ANOVA Table
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PDF
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YouTube
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SLR: Prediction vs. Confidence Intervals
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PDF
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YouTube
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Derivation of SLR Regression Coefficients
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PDF
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YouTube
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Variance of Regression Coefficients
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PDF
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YouTube
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Coefficient of Determination and Correlation Connection
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PDF
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YouTube
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Residuals
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PDF
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YouTube
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Diagnostic Plots
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PDF
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YouTube
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SLR Example: Continuous Predictor
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PDF
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YouTube
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SLR Example: Categorical Predictor
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PDF
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YouTube
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Transformations to Remove Heteroscedasticity
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PDF
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YouTube
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Multiple Linear Regression
The final theme of BIOS 6611 expands our linear regression framework to account for more than one predictor. This results in a variety of different applications and topics that are broken down further into subthemes below.
MLR Introduction
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Lecture Topic
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Slides
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Video Link
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Multiple Linear Regression (MLR): Motivation, Assumptions, Example
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PDF
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YouTube
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MLR: Diagnostic Plots and Multicollinearity
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PDF
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YouTube
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MLR: Inference on Independent Variables
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PDF
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YouTube
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Multiple Testing/Comparisons
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PDF
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YouTube
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Analysis of Variance (ANOVA) and Post-hoc Testing
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Lecture Topic
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Slides
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Video Link
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Coding Categorical Variables
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PDF
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YouTube
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One-Way ANOVA and Connections to Regression
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PDF
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YouTube
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Post-hoc Testing for ANOVA
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PDF
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YouTube
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Kruskal-Wallis: A Nonparametric ANOVA
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PDF
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YouTube
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Special Topics
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Lecture Topic
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Slides
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Video Link
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General Linear Hypothesis Testing
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PDF
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YouTube
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Confounders and Precision Variables
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PDF
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YouTube
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Mediation Models
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PDF
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YouTube
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Polynomial Regression
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PDF
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YouTube
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Interaction/Effect Modification
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PDF
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YouTube
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Model Selection Procedures
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PDF
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YouTube
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Variable Selection Considerations
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PDF
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YouTube
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Diagnostics for Outliers and Influential Points
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PDF
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YouTube
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Supplemental Material on Contrasts
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PDF
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Matrix Approaches to Regression
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Lecture Topic
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Slides
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Video Link
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Linear Regression in Matrix Format
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PDF
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YouTube
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Linear Regression with Matrices in SAS
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SAS
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YouTube
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Linear Regression with Matrices in R
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HTML
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YouTube
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MLE and Regression
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PDF
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YouTube
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Exponential Families and Generalized Linear Models
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PDF
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YouTube
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