BIOS.600.602
Hello! Welcome to BIOS 600, Introduction to Biostatistics, section 602. I am Nate Wiecha, a postdoctoral research trainee in Biostatistics here at Gillings School of Public Health. I’m looking forward to teaching this course!
This is the webpage for the course. The Canvas page will mainly be used to accept assignment submissions, host instructional lab videos, and store grading information. As a disclaimer, I will aim to have Canvas accurately compute cumulative grades, but this is error-prone and you should not rely on cumulative grades displayed in Canvas. You should calculate them yourselves using the assignment grades and the weighting in the syllabus.
I’ll be updating this website as the semester goes on with slides and assignments for each week, along with any updates or changes to the schedule/material.
Course syllabus: syllabus
Free tutor information*: tutor info
*Note Molly Hoch’s tutoring OH are now located in MCG 3101A.
Exam 1 info:
Exam 2 info:
- Topic list (updated March 23)
- Formula sheet
- Practice problems
- Practice problem solutions
Final exam info:
Where to find/submit materials/assignments:
Written lecture notes: Posted to Canvas under “Files”. Used to be on course website.
Homework assignments: posted on the course website (here). Organized by week in the weekly table.
Submitting homework assignments: course Canvas page -> Gradescope 1.3 tab
Lab assignments and templates: posted on the course website (here). Organized by week in the weekly table.
Lab videos: course Canvas page -> Panopto -> Lab recordings
Submitting labs: course Canvas page -> Gradescope 1.3 tab
Submitting participation exercises: course Canvas page -> Assignments tab
Here is the course schedule:
Week 0
| Topic | Slides | Assignments | Lab |
|---|---|---|---|
| Lecture 0: Welcome! |
Week 1 (Jan 12-16)
| Topic | Slides | Assignments | Lab |
|---|---|---|---|
| Lecture 1: What is statistical inference? | lab 1 | ||
| Lecture 2: The nature of data |
Week 2 (Jan 19-23)
| Topic | Slides | Assignments | Lab |
|---|---|---|---|
| Lecture 3: Probability basics | |||
| Lecture 4: Conditional probability and Bayes’ rule |
Week 2 (Jan 26-30)
Ice day: no class Tuesday Jan 27.
| Topic | Slides | Assignments | Lab |
|---|---|---|---|
| Data wrangling | |||
| Lecture 5: Diagnostic tests | HW 2 |
Week 3 (Feb 2-6)
| Topic | Slides | Assignments | Lab |
|---|---|---|---|
| Lecture 6: Discrete distributions | |||
| Lecture 7: Discrete distributions review, continuous distributions |
Week 4 (Feb 9-13)
| Topic | Slides | Assignments | Lab |
|---|---|---|---|
| More practice with tidyverse and ggplot2 | lab 4 | ||
| Lecture 8: Central Limit Theorem |
Week 9 (Feb 16-20)
| Topic | Slides | Assignments | Lab |
|---|---|---|---|
| Lecture 9: Confidence intervals | HW 4 |
Week 10 (Feb 23-27)
| Topic | Slides | Assignments | Lab |
|---|---|---|---|
| Lecture 10: Hypothesis Testing | lab 5 | ||
| Lecture 11: Comparing means |
Week 11 (March 2-6)
| Topic | Slides | Assignments | Lab |
|---|---|---|---|
| Lecture 12: Analysis of variance (ANOVA) | AE 03 | ||
| Lecture 13: Proportions |
Week 12 (March 9-13)
| Topic | Slides | Assignments | Lab |
|---|---|---|---|
| Lecture 14: Nonparametric methods | No lab assigned this week; HyungGyu will hold OH at lab time | ||
| Lecture 15: Power and sample size | AE 04 |
Week 13 (March 23-27)
| Topic | Slides | Assignments | Lab |
|---|---|---|---|
| Lecture 16: Comparing continuous variables | AE 05 | No lab assigned this week; HyungGyu will hold OH at lab time |
Week 14 (April 6-10)
| Topic | Slides | Assignments | Lab |
|---|---|---|---|
| Lecture 17: Linear regression | AE 06 | Lab 7 | |
| Lecture 18: Multiple linear regression |
Week 15 (April 13-17)
| Topic | Slides | Assignments | Lab |
|---|---|---|---|
| Lecture 19: Interactions and Collinearity | |||
| Lecture 20: Logistic regression |
Week 16 (April 20-24)
| Topic | Slides | Assignments | Lab |
|---|---|---|---|
| Lecture 21: More logistic regression | AE 07 |