STATS 101C · STAT 101CIntroduction to Statistical Models and Data Mining
Statistics · 4 units · Undergraduate upper division (100-199)
Recommended: course 101B. Designed for juniors/seniors. 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
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Requisites
Official UCLA wording
Enforced requisite: course 101A.
BruinTree reads · Prerequisite
confidence 1.00 · from textRequires
Everything that has to come before this course, not just the courses named in the requisite above.
STATS 101C
- STATS 101AIntroduction to Data Analysis and Regression
- STATS 10Introduction to Statistical Reasoning
- STATS 12Introduction to Statistical Methods for Geography and Environmental Studies
- ECON 41Probability and Statistics for Economists
- MATH 31BIntegration and Infinite Series
- 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
1 direct requisite. Showing 16 courses over 3 levels; the branches marked with a count carry on past it. Every course here opens its own tree.
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
STATS 101C
- STATS C116Applied Bayesian Social Statistics
- STATS 133Introduction to Text Mining Using R
- MATH M148Experience of Data Science
- STATS 184Societal Impacts of Data
- STATS C216Applied Bayesian Social Statistics
5 courses list this as a requisite. The whole downstream is here — 5 courses over 1 level. Every course here opens its own tree.