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STATS 100B · STAT 100BIntroduction to Mathematical Statistics

Statistics · 4 units · Undergraduate upper division (100-199)

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Survey sampling, estimation, testing, data summary, one- and two-sample problems.

P/NP or letter grading.

When it runs

Checking the Schedule of Classes…

Requisites

Official UCLA wording

Requisite: course 100A or Mathematics 170A or 170E.

BruinTree reads · Prerequisite

confidence 1.00 · from text
one of
  • STATS 100A
  • MATH 170A
  • MATH 170E

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Requires

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

STATS 100B

  • STATS 100AIntroduction to Probability
    • MATH 32BCalculus of Several Variables
      • MATH 31BIntegration and Infinite Series1 more beneath
      • MATH 32ACalculus of Several Variables1 more beneath
    • MATH 33ALinear Algebra and Applications
      • MATH 3BCalculus for Life Sciences Students1 more beneath
      • MATH 31BIntegration and Infinite Seriesanother path to it
      • MATH 32ACalculus of Several Variablesanother path to it
  • MATH 170AProbability Theory I
    • MATH 32BCalculus of Several Variablesanother path to it
    • MATH 33ALinear Algebra and Applicationsanother path to it
    • MATH 131AAnalysis
      • MATH 32BCalculus of Several Variablesanother path to it
      • MATH 33BDifferential Equations
  • MATH 170EIntroduction to Probability and Statistics 1: Probability
    • MATH 32BCalculus of Several Variablesanother path to it

3 direct requisites. 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 100B9 more beyond

  • STATS 100CLinear Models2 more beyond
    • STATS C151Experimental Design
    • STATS 170Introduction to Time-Series Analysis
    • BIOMATH M257Computational Methods for Biostatistical Research
    • STATS C173Applied Geostatistics
    • STATS M230Statistical Computing
    • BIOSTAT M215Survival Analysis
      • BIOSTAT 233Statistical Issues in Global Health
    • BIOMATH M280Statistical Computing
    • BIOSTAT M257Computational Methods for Biostatistical Research
  • STATS 102BIntroduction to Computation and Optimization for Statistics
  • BIOMATH M207ATheoretical Genetic Modeling
  • STATS 102CIntroduction to Monte Carlo Methods
  • STATS C116Applied Bayesian Social Statistics
  • BIOSTAT 125The Science of Why: Causal Inference for Public Health
  • STATS 140XPCollaboration in Data Science
    • STATS 141XPPractice of Data Science
  • STATS 143Introduction to Research in Statistics
  • ECON 103Introduction to Econometrics22 more beyond
    • ECON 103LEconometrics Laboratory
      • ECON 103Introduction to Econometricsanother path to it
      • ECON 109CAdvanced Sequence: Computational Economicsanother path to it
      • ECON 109DAdvanced Sequence: Econometric Theoryanother path to it
      • ECON 123Forecasting of Asset Prices and Portfolio Design
      • ECON 123LForecasting of Asset Prices and Portfolio Design Laboratory
    • ECON 104Data Science for Economists
      • ECON 104LData Science for Economists Laboratoryanother path to it
      • ECON 144Economic Forecasting
    • ECON 104LData Science for Economists Laboratory
      • ECON 104Data Science for Economistsanother path to it
      • ECON 144Economic Forecastinganother path to it
    • ECON 109CAdvanced Sequence: Computational Economics
    • ECON 109DAdvanced Sequence: Econometric Theory
      • ECON 109DLAdvanced Sequence: Econometric Theory Laboratoryanother path to it
    • ECON 109DLAdvanced Sequence: Econometric Theory Laboratory
      • ECON 109DAdvanced Sequence: Econometric Theoryanother path to it
    • ECON 109EAdvanced Sequence: Applied Empirical Economics
    • ECON 111Theories of Development
      • PUB PLC CM171International Development
      • ECON 111LTheories of Development Laboratory
      • ECON 112Policies for Economic Development
      • ECON M112AInternational Development
  • STATS C145History and Theory of Statistics
  • STATS 147Data Technologies for Data Scientists
  • HUM GEN M207ATheoretical Genetic Modeling
  • STATS M148Experience of Data Science
  • STATS 153Hierarchical Linear Modeling
  • MATH M148Experience of Data Science

26 courses list this as a requisite. Showing 48 courses over 3 levels; the branches marked with a count carry on past it. Every course here opens its own tree.

  • Fall 2025
  • Winter 2026
  • Spring 2026
  • Summer 2026
  • Fall 2026
  • Winter 2027
  • Spring 2027

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