Expanded Course Descriptions

Course description summaries can be found in the General Catalog.  Below are links to expanded course descriptions and outlines.  Please note that some of the expanded descriptions are still being updated.

Lower Division Courses (1-99)

10. Statistical Thinking
12. Introduction to Discrete Probability
13. Elementary Statistics
15A. Introduction to Statistical Data Science I
15B. Introduction to Statistical Data Science II
15C. Introduction to Statistical Data Science III
32. Gateway to Statistical Data Science
35A. Statistical Data Science I
35B. Statistical Data Science II
35C. Statistical Data Science III

Upper Division Courses (100-199)

100. Applied Statistics for Biological Sciences
101. Advanced Applied Statistics for the Biological Sciences
103. Applied Statistics for Business and Economics
104. Applied Statistical Methods: Nonparametric Statistics
106. Applied Statistical Methods: Analysis of Variance
108. Applied Statistical Methods: Regression Analysis
109. Fundamentals of Statistical Learning
130A. Mathematical Statistics: Brief Course
130B. Mathematical Statistics: Brief Course
131A. Introduction to Probability Theory 
131B. Introduction to Mathematical Statistics
131C. Introduction to Mathematical Statistics
135. Multivariate Data Analysis
137. Applied Time Series Analysis
138. Analysis of Categorical Data
141A. Fundamentals of Statistical Data Science
141B. Data and Web Technologies for Data Analysis
141C. Big Data and High Performance Statistical Computing
142A. Statistical Learning I
142B.  Statistical Learning II
144. Sampling Theory of Surveys
145. Bayesian Statistical Inference
160. Practice in Statistical Data Science

Graduate Level Courses (200-299)

200A. Introduction to Probability Theory
200B. Introduction to Mathematical Statistics I
200C. Introduction to Mathematical Statistics II
201. SAS Programming for Statistical Analysis
205. Statistical Methods for Research with SAS
206. Statistical Methods for Research I
207. Statistical Methods for Research II
208. Statistical Methods in Machine Learning
209. Optimization for Big Data Analytics
220. Data & Web Technologies for Data Analysis
221. Big Data & High Performance Statistical Computing
222. Biostatistics: Survival Analysis
223. Biostatistics: Generalized Linear Models 
224. Analysis of Longitudinal Data 
225. Clinical Trials 
226. Statistical Methods for Bioinformatics
231A. Mathematical Statistics I
231B. Mathematical Statistics II
231C. Mathematical Statistics III
232A. Applied Statistics I
232B. Applied Statistics II
232C. Applied Statistics III
233. Design of Experiments
235A. Probability Theory
235B. Probability Theory
235C. Probability Theory
237A. Time Series Analysis
237B. Time Series Analysis
238. Theory of Multivariate Analysis
240A. Nonparametric Inference
240B. Nonparametric Inference
241. Asymptotic Theory of Statistics
242. Introduction to Statistical Programming
243. Computational Statistics
250. Topics in Applied and Computational Statistics
251. Topics in Statistical Methods and Models
252. Advanced Topics in Biostatistics
260. Statistical Practice and Data Analysis 
280. Orientation to Statistical Research
290. Seminar in Statistics

Professional Courses (300-399)

390. Methods of Teaching Statistics
396. Teaching Assistant Training Practicum