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STATS 15 · STAT 15Introduction to Data Science

Statistics · 5 units · Undergraduate lower division (0-99)

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Not open to students with credit for course 10, 12, 13, or former course 10H, 11, or 14. Introduction to data science, including data management, data modeling, data visualization, communication of findings, and reproducible work.

P/NP or letter grading.

When it runs

  • Fall 2025
  • Fall 2026

Scheduled, not typical — from UCLA’s Schedule of Classes, which publishes Fall 2025 through Spring 2027 and nothing before it.

Requisites

Official UCLA wording

Preparation: three years of high school mathematics.

BruinTree reads · Preparation

needs reviewconfidence 0.00 · from text

BruinTree could not read this requirement — see UCLA’s wording above.

  • · could not read "three years of high school mathematics" (no course number found)
  • · no course reference could be read from this requisite

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About STATS 15. We read UCLA’s requisite wording by machine, and it gets things wrong.

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Requires

Everything that has to come before this course, not just the courses named in the requisite above.

Nothing — this is an entry point.

Unlocks

What this course is a requisite for, and what those courses lead to in turn.

STATS 15

  • STATS 20Introduction to Statistical Programming with R3 more beyond
    • STATS 21Python and Other Technologies for Data Science
      • STATS 152Environmental Statisticsanother path to it
      • STATS C160Causal Inference for Health Dataanother path to it
      • MATH 156Machine Learning3 more beyond
      • STATS C167Introduction to Databasesanother path to it
    • STATS 101AIntroduction to Data Analysis and Regressionanother path to it
    • MATH 42Introduction to Data-Driven Mathematical Modeling: Life, Universe, and Everything
      • MATH 118Mathematical Methods of Data Theory1 more beyond
    • STATS 102AIntroduction to Computational Statisticsanother path to it
    • STATS 152Environmental Statisticsanother path to it
    • POL SCI M170XCausality X
    • STATS M169Causality X
    • STATS 411Multivariate Statistical Analysis
  • STATS 101AIntroduction to Data Analysis and Regression3 more beyond
    • STATS 101BIntroduction to Design and Analysis of Experiment
      • STATS C116Applied Bayesian Social Statisticsanother path to it
      • STATS 140XPCollaboration in Data Science1 more beyond
      • STATS 143Introduction to Research in Statisticsanother path to it
      • STATS 153Hierarchical Linear Modelinganother path to it
      • STATS C173Applied Geostatistics
    • STATS 101CIntroduction to Statistical Models and Data Mining
      • STATS C116Applied Bayesian Social Statisticsanother path to it
      • STATS 133Introduction to Text Mining Using Ranother path to it
      • MATH M148Experience of Data Scienceanother path to it
    • 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 102AIntroduction to Computational Statistics
    • STATS 131Python and Other Technologies for Data Analysis
    • STATS 133Introduction to Text Mining Using R
    • STATS 143Introduction to Research in Statistics
    • STATS C167Introduction to Databases
    • STATS C267Introduction to Databases
  • STATS C116Applied Bayesian Social Statistics
  • STATS 152Environmental Statistics
  • STATS C216Applied Bayesian Social Statistics

6 courses list this as a requisite. Showing 40 courses over 3 levels; the branches marked with a count carry on past it. Every course here opens its own tree.