Stanford Root

Schedule

Stanford Root

Schedule

STATS 200

Introduction to Theoretical Statistics

UNITS:3-4
GRADING:Letter or Credit/No Credit
LEVEL:Graduate
GER:—

Modern statistical concepts and procedures derived from a mathematical framework. Statistical inference, decision theory; point and interval estimation, tests of hypotheses; Neyman-Pearson theory. Bayesian analysis; maximum likelihood, large sample theory. Prerequisite: STATS STATS 118 or equivalent. See https://statistics.stanford.edu/course-equiv for equivalent courses in other departments that satisfy these prerequisites.

Syllabus for selected term:
View Autumn 2026 Syllabus

Sections

2 Terms
Lecture 1Open
ID: 6987
0 / 125 enrolled
DAYS:Monday, Wednesday, Friday
TIME:3:30 PM – 4:20 PM
LOCATION:Gates B1
INSTRUCTOR:
Kim, Gene
units
Lecture 2Open
ID: 7222
0 / 190 enrolled
DAYS:Monday, Wednesday, Friday
TIME:3:30 PM – 4:20 PM
LOCATION:Gates B1
INSTRUCTOR:
Kim, Gene
units
Discussion 1Open
ID: 7407
0 / 20 enrolled
DAYS:Tuesday
TIME:10:30 AM – 11:20 AM
LOCATION:100-101K
units
Discussion 2Open
ID: 7408
0 / 20 enrolled
DAYS:Tuesday
TIME:11:30 AM – 12:20 PM
LOCATION:ANKO 008
units
Discussion 3Open
ID: 7409
0 / 20 enrolled
DAYS:Tuesday
TIME:12:30 PM – 1:20 PM
LOCATION:Lathrop 298
units
Discussion 4Open
ID: 7410
0 / 20 enrolled
DAYS:Tuesday
TIME:1:30 PM – 2:20 PM
LOCATION:STLC 118
units
Discussion 5Open
ID: 7571
0 / 20 enrolled
DAYS:Tuesday
TIME:2:30 PM – 3:20 PM
LOCATION:Gates100
units
Discussion 6Open
ID: 12513
0 / 20 enrolled
DAYS:Tuesday
TIME:3:30 PM – 4:20 PM
LOCATION:Littlefield 104
units

STATS 200: Introduction to Theoretical Statistics

3-4 units · Letter or Credit/No Credit

Modern statistical concepts and procedures derived from a mathematical framework. Statistical inference, decision theory; point and interval estimation, tests of hypotheses; Neyman-Pearson theory. Bayesian analysis; maximum likelihood, large sample theory. Prerequisite: STATS 118 or equivalent. See https://statistics.stanford.edu/course-equiv for equivalent courses in other departments that satisfy these prerequisites.

Offered in Autumn 2026, Winter 2027 at Stanford University.

Autumn 2026 sections

  • Discussion — Tuesday 3:30 PM – 4:20 PM — Littlefield 104 (Graduate)
  • Discussion — Tuesday 2:30 PM – 3:20 PM — Gates100 (Graduate)
  • Discussion — Tuesday 1:30 PM – 2:20 PM — STLC 118 (Graduate)
  • Discussion — Tuesday 12:30 PM – 1:20 PM — Lathrop 298 (Graduate)
  • Discussion — Tuesday 11:30 AM – 12:20 PM — ANKO 008 (Graduate)
  • Discussion — Tuesday 10:30 AM – 11:20 AM — 100-101K (Graduate)
  • Lecture — Monday Wednesday Friday 3:30 PM – 4:20 PM — Gates B1 — Kim, Gene (Graduate)
  • Lecture — Monday Wednesday Friday 3:30 PM – 4:20 PM — Gates B1 — Kim, Gene (Graduate)

Winter 2027 sections

  • Lecture — Monday Wednesday Friday 9:30 AM – 10:20 AM — Walther, Guenther (Graduate)
  • Lecture — Monday Wednesday Friday 9:30 AM – 10:20 AM — Walther, Guenther (Graduate)
  • Discussion — Thursday 11:30 AM – 12:20 PM (Graduate)
  • Discussion — Thursday 10:30 AM – 11:20 AM (Graduate)
  • Discussion — Thursday 2:30 PM – 3:20 PM (Graduate)
  • Discussion — Thursday 4:30 PM – 5:20 PM (Graduate)
  • Discussion — Thursday 3:30 PM – 4:20 PM (Graduate)
  • Discussion — Thursday 9:30 AM – 10:20 AM (Graduate)

More STATS courses

  • STATS 116X: Theory of Probability (accelerated)
  • STATS 117: Introduction to Probability Theory
  • STATS 118: Probability Theory for Statistical Inference
  • STATS 141: Introduction to Statistics for Biology (BIO 141)
  • STATS 191: Introduction to Applied Statistics
  • STATS 199: Independent Study
  • STATS 200Q: Philosophical Foundations of Statistics (DATASCI 200Q)
  • STATS 202: Statistical Learning and Data Science
  • STATS 203: Regression Models and Analysis of Variance
  • STATS 205: Introduction to Nonparametric Statistics
  • STATS 207: Time Series Analysis (STATS 307)
  • STATS 208: Resampling Methods: Bootstrap, Cross Validation and Beyond

All STATS courses · All departments