What you will be able to do
- Describe a data set with the right summary for its type of variable
- Explain what a sampling distribution is and why it makes inference possible
- Build and interpret a confidence interval, and read a p-value without the common mistakes
- Choose a basic test for comparing groups, for paired data and for categorical outcomes
- Read correlation and simple regression output, and know what logistic regression and survival analysis answer
- Explain power and sample size, and why many comparisons inflate false positives
- Read a results table in a published paper with confidence
What the course will cover
Part 1. Describing data
- Types of data and how to summarize them
- Distributions
- Probability
Part 2. From sample to population
- Sampling and the sampling distribution
- Estimation and confidence intervals
- The logic of hypothesis testing
Part 3. Comparing groups
- One-sample and two-sample comparisons
- Paired data
- Analysis of variance (ANOVA)
- Chi-square and other methods for categorical data
- Nonparametric methods
Part 4. Relationships and study planning
- Correlation
- Simple linear regression
- An introduction to logistic regression (concepts only)
- Survival concepts
- Power and sample size
- Multiple comparisons
- Reading a results table
The lesson list may change as the course is built.
Where it fits
Principles of Biostatistics sits beside Principles of Epidemiology as a core course. It prepares learners for Design of Clinical Studies and for later courses on statistical methods in epidemiology.