Spring 2027

Mathematical Statistics II

Advanced mathematical statistics covering estimation, hypothesis testing, confidence regions, decision theory, and likelihood ratio methods with current research topics.

offering recorded4 credits
Recorded instructors · Spring 2027 Jun Shao

Summary

1 / 3

Recent recorded grades — Spring 2024: 3.70 GPA, 90.0% A/AB (n=20 letter grades); Spring 2025: 3.64 GPA, 81.8% A/AB (n=22 letter grades); Spring 2026: 3.54 GPA, 64.3% A/AB (n=14 letter grades).

What you’ll be able to do

  • Define and distinguish different notions of optimality in point estimation, hypothesis testing, and confidence sets.

  • Apply standard techniques to derive optimal estimators, hypothesis tests, and confidence sets.

  • Study statistical inference procedures for parametric and non-parametric models.

  • Investigate asymptotic analysis of point estimators, hypothesis tests, and confidence sets.

  • Understand and critique current research in mathematical statistics.

Source: UW Guide 1 UW Guide 2

Grade history

↗
average GPA
letter grades
A
AB
B
BC
C
D
F

All recorded terms · compare terms & instructors

Prerequisites

Course map

STAT/​MATH 709

MATH/STAT 710 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

Recent recorded grades — Spring 2016: 3.53 GPA, 68.8% A/AB (n=16 letter grades); Spring 2018: 3.52 GPA, 68.2% A/AB (n=22 letter grades); Spring 2019: 3.52 GPA, 70.0% A/AB (n=20 letter grades).

Historical instructors & teaching patterns

JUN SHAO is recorded teaching in Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2016, Spring 2018, Spring 2019. 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 / 300
DIS 311Classroom Instruction0 / 300
LEC 001Classroom Instruction0 / 300
DIS 311Classroom Instruction0 / 300

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

Recent recorded grades — Spring 2024: 3.70 GPA, 90.0% A/AB (n=20 letter grades); Spring 2025: 3.64 GPA, 81.8% A/AB (n=22 letter grades); Spring 2026: 3.54 GPA, 64.3% A/AB (n=14 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Estimation theory, efficiency, and likelihood ratio theory
  • Neyman-Pearson hypothesis testing and confidence regions
  • Decision theory and current research in mathematical statistics

Skills

  • Distinguish notions of optimality in point estimation, hypothesis testing, and confidence sets.
  • Derive optimal estimators, hypothesis tests, and confidence sets using standard techniques.
  • Investigate asymptotic analysis of statistical inference procedures.

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
MATH/STAT 710 · Spring 2027

Mathematical Statistics II

Recorded 2026-10-14
MATH/STAT 710 · Spring 2027

Mathematical Statistics II

Recorded 2026-10-14
Raw records 
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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 
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  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
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