STATS 101A · STAT 101AIntroduction to Data Analysis and Regression
Statistics · 4 units · Undergraduate upper division (100-199)
Recommended: course 102A. Applied regression analysis, with emphasis on general linear model (e.g., multiple regression) and generalized linear model (e.g., logistic regression). Special attention to modern extensions of regression, including regression diagnostics, graphical procedures, and bootstrapping for statistical influence.
P/NP or letter grading.
When it runs
Checking the Schedule of Classes…
Requisites
Official UCLA wording
Requisites: one course from course 10, 12, 13, 15, Economics 41, or Psychology 100A, or score of 4 or higher on Advanced Placement Statistics Examination, and course 20.
Requires
Everything that has to come before this course, not just the courses named in the requisite above.
STATS 101A
- STATS 10Introduction to Statistical Reasoning
- STATS 12Introduction to Statistical Methods for Geography and Environmental Studies
- ECON 41Probability and Statistics for Economists
- STATS 13Introduction to Statistical Methods for Life and Health Sciences
- STATS 15Introduction to Data Science
- PSYCH 100APsychological Statistics
- COMPTNG 10AIntroduction to Programming
- PSYCH 10Introductory Psychology
- STATS 20Introduction to Statistical Programming with R
- STATS 12Introduction to Statistical Methods for Geography and Environmental Studiesanother path to it
7 direct requisites. The whole upstream is here — 17 courses over 3 levels. Every course here opens its own tree.
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
STATS 101A
- STATS 101BIntroduction to Design and Analysis of Experiment
- STATS C116Applied Bayesian Social Statistics
- STATS 140XPCollaboration in Data Science
- STATS 141XPPractice of Data Science
- STATS 143Introduction to Research in Statistics
- STATS C173Applied Geostatistics
- STATS 101CIntroduction to Statistical Models and Data Mining
- STATS 133Introduction to Text Mining Using R
- STATS C216Applied Bayesian Social Statistics
- MATH M148Experience of Data Science
- STATS C151Experimental Design
- STATS 153Hierarchical Linear Modeling
- STATS C160Causal Inference for Health Data
- STATS 170Introduction to Time-Series Analysis
- STATS 184Societal Impacts of Data
- STATS 411Multivariate Statistical Analysis
- STATS 422Data Visualization
- STATS 423Longitudinal Data Analysis
- STATS 424Teamwork and Leadership in Data Science
12 courses list this as a requisite. The whole downstream is here — 24 courses over 3 levels. Every course here opens its own tree.