Schedule

Schedule for Math 58B, Introduction to Biostatistics, Spring 2026

Here’s your roadmap for the semester! Each week, follow the general process outlined below:

• Before class on Monday, read the suggested article

• Enjoy the notes / readings

• Attend class, review the worksheet and solution.

• Complete the Lab and HW assignments

  • Lab due every Tuesday by 11:59pm
  • HW due every Thursday by 11:59pm

• Discuss the reflection questions and ethics considerations (see class notes) with your classmates, mentor, and professor

• IMS: Introduction to Modern Statistics by Çetinkaya-Rundel and Hardin.

• ISCAM: Investigating Statistics, Concepts, Applications, and Methods by Chance and Rossman. Many of the examples come from ISCAM, a pdf of which can be purchased for $5.

  • ISCAM applets
  • StatKey (boostrapping) applets

date	topic	agenda	readings	article (Mon)	assignments
Week 1 1.19.26	Intro + variables & studies SLR	• course info • tests • studies • causation	Introduction Studies ISCAM 1.1 IMS 1 + 2	none Felicity Enders	WU1 WU2 HW 0 pdf HW 0 Rmd
Week 2 1.26.26	Correlation + Least squares	• correlation • linear model • R^2	Cor Least Sq ISCAM 5.6, 5.7, 5.8 IMS 7 guess corr least sq	AstraZeneca W.E.B. Du Bois
Week 3 2.2.26	Hyp Test + Randomization Test	• structure of hypothesis testing	Tests 2x2 Rand IMS 11
Week 4 2.9.26	Bootstrapping	• boot samp dist • boot CI	Bootstrapping Boot CIs StatKey CIs IMS 12		Quiz 1 on 2/11/26
Week 5 2.16.26	normality + CLT	• normal dist • CLT • Z-score • empirical rule • conf int • norm prob • hyp test	CLT Norm dist Samp Dist IMS 13
Week 6 2.23.26	Errors + Power + Sampling	• Type I error • Type II error • Power • biased samples	Errors Sampling Power IMS 14 + 2		Quiz 2 on 2/25/26
Week 7 3.2.26	Rel Risk + Odds Ratios	• RR • OR	diff props RR OR ISCAM 3.9-3.11 IMS 17
Week 8 3.9.26	Case-control + cohort studies	• Case-control • Cohort	RR OR	there is lab on 3.13.26	Quiz 3 on 3/11/26
3.16.26	spring break
Week 9 3.23.26	χ^2 Test	• expected counts • X^2 statistic • χ^2 test	χ^2 Test ISCAM 3.2 IMS 18	no lab on 3.27.26
Week 10 3.30.26	1 mean + pred interval	• dist of X-bar • SE(X-bar) • t-test of μ • t-CI for μ • PI for X_{n+1}	1 mean pred int IMS 19
3.24.26	Proj 1: Pilot				Proj 1: Pilot
Week 11 4.6.26	2 means + t-proced	• dist of X-bar_1 - X-bar_2 • SE(X-bar_1 - X-bar_2) • t-test of μ_1 - μ_2 • randomization test of μ_1 - μ_2 • t-CI for μ_1 - μ_2 • bootstrap CI for μ_1 - μ_2	2 means 2 samples IMS 20		Quiz 4 on 4/8/26
3.31.26	Proj 2: Power Analysis				Proj 2: Power Analysis
Week 12 4.13.26	ANOVA	• MSG • MSE • F-test	ANOVA Inf on β_1 slopes IMS 22 IMS 24
Week 13 4.20.26	Inference β_1 + Tech cond	• SE(β_1) • residual plots	Tech Cond		Quiz 5 on 4/22/26
4.14.26	Proj 3: Analysis				Proj 3: Preliminary Analysis
Week 14 4.27.26	MLR	• multiple X	MLR IMS 25
Week 15 5.4.26					Quiz 6 on 5/6/26
5.5.26	Proj 4: Full draft				Proj 4: Full draft
5.7 or 14.26	Proj Presentation				Proj Presentation
5.14.26	Proj 5: Final Project				Proj 5: Final Project