Overview

Biostatistics course

Bill Perry

This course will serve as an introduction to reproducible data analysis using R. Specifically the goal is to introduce students to all facets of managing a research project with an emphasis on:

  • Developing questions form observations, hypotheses, and predictions for testing statistically
  • Designing data workflows with data entry, curation, QA/QC, and cleaning
  • Using a controlled vocabulary and organized project structure and documenting the metadata for the project
  • Importing data into R and doing calculations and transformations
  • Visualizing data using ggplot
  • Understanding how to decide on statistical tests that are appropriate - T-Tests - parametric and nonparametric
-   Correlations
-   Linear models
    -   linear regression
    -   multiple linear regression
    -   ANOVA
    -   ANCOVA
    -   GLM and logistic regression
-   Analyzing Frequencies
-   Multivariate Statistics
    -   Principal component analysis
    -   NMDS
    -   Cluster analysis

In the main webpage I have provided links to all the information you will need:

  • links to readings that should be read prior to class
  • powerpoint lectures that should be reviewed prior to class
  • in-class activities that will actively cover the materials in the powerpoints
  • weekly homework to do the in class activities on your own using different data
  • assignments that form the crux of the grade and there 4 of them