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Dibs Fall 2026

BIOSTAT

Biostatistics

49 courses on record · 5 with sections in Fall 2026

Live section data currently covers GE courses; the rest is filled in by a nightly pass, so this department is likely running more than is listed here.

49 courses

Upper division 5

Upper division courses in Biostatistics
Course Title Predicted GPA This term
100 Introduction to Biostatistics 3.80 n=210 —
100A Introduction to Biostatistics 3.72 n=1,094 —
100B Introduction to Biostatistics 3.96 n=196 —
120 Biostatistics in Public Health 3.59 n=90 —
121 Biostatistics in Public Health 3.81 n=10 small sample —

Graduate 44

Graduate courses in Biostatistics
Course Title Predicted GPA This term
200A Methods in Biostatistics A 3.78 n=77 1 section
200B Methods in Biostatistics B 3.83 n=101 —
200C Methods in Biostatistics C 3.74 n=55 —
201A Introduction to Biostatistics 3.81 n=255 2 sections
201B Topics in Applied Regression 3.72 n=150 —
202A Mathematical Statistics A 3.68 n=72 —
202B Mathematical Statistics B 3.70 n=70 —
202C Theory of Bayesian Statistics 3.93 n=44 —
203A Introduction to Data Management and Statistical Computing 3.93 n=159 —
203B Introduction to Data Science 3.76 n=235 —
203C Introduction to Data Science in Python 3.65 n=110 —
211A Topics in Applied Regression 3.92 n=33 —
211B Topics in Applied Regression 3.70 n=30 —
212A Statistical Learning A 3.66 n=113 —
212B Statistical Learning B 3.75 n=111 —
213 Introduction to Computational Methods in Biostatistics 3.95 n=27 —
214 Finite Population Sampling no grade history —
M215 Survival Analysis 3.87 n=57 —
216 Mathematical Methods for Biostatistics 3.73 n=71 1 section
218 Observational Health Data Science and Informatics 3.96 n=43 —
231 Statistical Power and Sample Size Methods for Health Research 3.91 n=63 —
M232 Statistical Analysis of Incomplete Data 3.89 n=11 small sample —
M234 Applied Bayesian Inference 3.95 n=112 —
M235 Causal Inference 3.92 n=41 —
M236 Longitudinal Data 3.79 n=121 —
M238 Methodology of Clinical Trials 3.85 n=12 small sample —
241 Spatial Modeling and Data Analysis for Health Sciences 3.91 n=22 —
244 Master's Seminar and Research Resources for Graduating Biostatistics MS Students 3.97 n=53 —
245 Advanced Seminar: Biostatistics no letter grades 1 section
246 Doctoral Students Seminar no letter grades —
250A Linear Statistical Models 3.80 n=23 1 section
250B Linear Statistical Models 3.79 n=12 small sample —
250C Multivariate Biostatistics 3.85 n=12 small sample —
257 Computational Methods for Biostatistical Research 3.90 n=14 small sample —
M257 Computational Methods for Biostatistical Research 3.88 n=23 —
276 Inferential Techniques that Use Simulation 3.93 n=20 —
285 Advanced Topics: Recent Developments 3.90 n=47 —
400 Field Studies in Biostatistics 3.93 n=21 —
401 Data Science Capstone 3.89 n=68 —
402A Principles of Biostatistical Consulting 3.96 n=41 —
402B Biostatistical Consulting no grade history —
M403B Computer Management and Analysis of Health Data Using SAS no grade history —
406 Applied Multivariate Biostatistics 3.92 n=125 —
409 Doctoral Statistical Consulting Seminar no grade history —

“Predicted” is shrunk toward the department average, so a course taught once to a dozen students sits near the department mean rather than at whatever those twelve happened to get. The figure is always shown — small sample marks where it rests mostly on that prior.