2025 Fall
DATA C131A 101 - LAB 101
Formerly Statistics 131A
Statistical Methods for Data Science
Class #:24679
Units: 4
Instruction Mode:
In-Person Instruction
Offered through
Data Science Undergraduate Studies
Current Enrollment
Total Open Seats:
0
Enrolled: 0
Waitlisted: 0
Capacity: 0
Waitlist Max: 0
No Reserved Seats
Hours & Workload
3 hours of instructor presentation of course materials per week, 7 hours of outside work hours per week, and 2 hours of instructional experiences requiring special laboratory equipment and facilities per week.
Course Catalog Description
This course teaches a broad range of statistical methods that are used to solve data problems. Topics include group comparisons and ANOVA, standard parametric statistical models, multivariate data visualization, multiple linear regression, logistic regression and classification, regression trees and random forests. An important focus of the course is on statistical computing and reproducible statistical analysis. The course and lab include hands-on experience in analyzing real world data from the social, life, and physical sciences. The R statistical language is used.
Rules & Requirements
Requisites
- DATA/COMPSCI/INFO/STAT C8 or STAT 20; and MATH 1A, MATH 51, MATH 16A, or MATH 10A/10B. Strongly recommended corequisite: STAT 33A or STAT 133.
Repeat Rules
Course is not repeatable for credit.
Reserved Seats
Current Enrollment
No Reserved Seats
Textbooks & Materials
See class syllabus or https://calstudentstore.berkeley.edu/textbooks for the most current information.
Guide to Open, Free, & Affordable Course Materials