Spring 2027

Introduction to Theory and Methods of Mathematical Statistics II

Introduction to Theory and Methods of Mathematical Statistics II covers unbiased estimation, MLE, confidence intervals, hypothesis tests, Neyman-Pearson lemma, LRT, regression, and ANOVA.

offering recorded3 credits
Recorded instructors · Spring 2027 No instructors listed

Summary

1 / 6

Past student reviews · Bo Yang

The grade was based on about five homework assignments and three exams. One student found the material not difficult but noted it was taught extremely slowly.

What you’ll be able to do

  • Be able to use probability theory to understand and utilize three principal tools of statistical inference: point estimators, confidence intervals, and hypothesis tests.

  • Understand and be able to use standard statistical procedures for analyzing numerical data in certain contexts. These include inference for the mean based on a single random sample; comparing two means based on two random samples; Analysis of Variance; simple linear regression.

  • Understand and be able to use standard statistical procedures for analyzing binary and categorical data in certain contexts. These include one- and two-sample inference for proportions, and the analysis of one- and two-way contingency tables for multi-category data.

  • Identify the assumptions behind statistical procedures and understand their importance. Be able to recognize when techniques based on standard reference distributions (normal, chi-square, T- and F-distribution) are valid or not, and be able to utilize certain alternatives such as exact or nonparametric methods when they are required or preferable.

Source: UW Guide

Grade history

↗
average GPA
letter grades
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All recorded terms · compare terms & instructors

Prerequisites

Course map

STAT/​MATH 309,STAT 311,STAT/​MATH 431,MATH 531, or graduate/professional standing

STAT 312 used by

“Used by” includes alternatives; linked courses may have other requirements. This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree

Professors

Spring 2027

No instructors recorded for this selection.

Historical instructors & teaching patterns

BO YANG is recorded teaching in Spring 2017, Fall 2018. Recorded history may be incomplete and does not establish a future schedule.

DEREK BEAN is recorded teaching in Fall 2014, Spring 2019, Fall 2019, Fall 2020. Recorded history may be incomplete and does not establish a future schedule.

GONZALO CONTADOR is recorded teaching in Fall 2017. Recorded history may be incomplete and does not establish a future schedule.

ISMOR FISCHER is recorded teaching in Fall 2016, Spring 2017, Fall 2017, Spring 2018, Fall 2018, Spring 2020. Recorded history may be incomplete and does not establish a future schedule.

KAM-WAH TSUI is recorded teaching in Spring 2016. Recorded history may be incomplete and does not establish a future schedule.

MUHONG GAO is recorded teaching in Fall 2019. Recorded history may be incomplete and does not establish a future schedule.

NICHOLAS STEPHEN KEULER is recorded teaching in Fall 2010, Fall 2011. Recorded history may be incomplete and does not establish a future schedule.

NIMAL WICKREMASINGHE is recorded teaching in Spring 2023, Fall 2023, Spring 2024. Recorded history may be incomplete and does not establish a future schedule.

XIAOWU DAI is recorded teaching in Spring 2018, Fall 2018, Spring 2019. Recorded history may be incomplete and does not establish a future schedule.

YAOGUO XIE is recorded teaching in Spring 2016. Recorded history may be incomplete and does not establish a future schedule.

YONGSU LEE is recorded teaching in Spring 2019, Fall 2019, Spring 2020. Recorded history may be incomplete and does not establish a future schedule.

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Spring 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction0 / 660

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.

Meeting source records
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Student experience

the class

Past student reviews · Nicholas Keuler, Ismor Fischer

Students described the course as easy when the instructor explained material clearly, such as Nicholas Keuler using examples or Ismor Fischer being good at explaining concepts.

Recent recorded grades — Spring 2024: 3.64 GPA, 78.6% A/AB (n=14 letter grades); Spring 2025: 3.25 GPA, 50.0% A/AB (n=6 letter grades); Spring 2026: 3.57 GPA, 71.4% A/AB (n=7 letter grades).

difficulty & workload

Past student reviews · Bo Yang

The grade was based on about five homework assignments and three exams. One student found the material not difficult but noted it was taught extremely slowly.

Past student reviews · Derek Bean

A student found Derek Bean's handwriting illegible and teaching messy, forcing them to self-study from the textbook. They considered it the hardest course they had taken.

Topics

  • Statistical inference methods including estimation, hypothesis testing, regression, and ANOVA.

Skills

  • Apply unbiased estimation, maximum likelihood estimation, confidence intervals, hypothesis testing, Neyman-Pearson lemma, likelihood ratio tests, regression, and ANOVA.
  • Use probability theory to utilize point estimators, confidence intervals, and hypothesis tests.

Grades

Latest available · Spring 2026— not enough history to project Spring 2027.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Spring 2026

More grade details Grade mix, volume & source data

Not enough comparable courses for Spring 2027 in UW–Madison.

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

Observations at scan time; dates do not imply when a catalog change took effect.

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Selected offering source records
STAT 312 · Spring 2027

Introduction to Theory and Methods of Mathematical Statistics II

Recorded 2026-10-14
Raw records 
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  {
    "run_id": "20261014T203208-0851c9a1",
    "semester": "1274",
    "observed_at": "2026-10-14 17:50:09.728220+00:00",
    "offering_id": "1274:932:018444",
    "course_id": "STAT 312",
    "course_uid": "course_24942ca6acb3a153de2907d5",
    "term_id": "1274",
    "source_course_id": "018444",
    "source_subject_id": "932",
    "title": "Introduction to Theory and Methods of Mathematical Statistics II",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Fall, Spring"
  }
]
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Student reviews

Original comments behind the course and instructor summaries.

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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

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Dataset & model

Recorded 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1
Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "569ee4596bcfafa95956a8181a818432ce393dbc1e7f89987beebeb00c5ecf31",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}