Historical instructor

FANGFANG WANG

Adjusted rating
RMP difficulty
captured reviews
About this rating

Raw average: 3.00/5 from 2 quality ratings. The adjusted rating blends this with the UW review average (3.66/5), weighted as 20 additional ratings. Smaller samples stay closer to that average. Each captured review is counted once in the prior; this does not correct who chooses to leave a review.

RMP profile ↗ · All captured review dates; profile matched by name.

What students say

Original student reviews · all captured dates

Quality 3/5Difficulty 4/5
Lectures had too much content in too little time. Stuff was covered in one lecture that I had learned in an entire course. I just tuned out and taught myself the stuff that was relevant for the homework (which was really CS heavy)
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Quality 3/5Difficulty 5/5
Homework is really long, vague, programming assignments that are huge parts of the grade. There are no exams but there are some quizzes and a final project.
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Personal experiences, not a representative survey. Profile matching and captured coverage are shown in the source details.

Classes with FANGFANG WANG

Introduction to computational statistics focusing on inference principles for complex data structures using numerical methods like Monte Carlo and optimization.

No offering record · Spring 2019

with this instructor · course overall, matching historical terms

historical GPA · grades

Spring 2018–Spring 2019 · limited sample

Recorded teaching history

Distinct courses recorded per term

Explore courses taught by this instructor →
Browse recorded courses
TermCourseTitle
Spring 2019COMPSCI/STAT 471Introduction to Computational Statistics
Fall 2018STAT 701Applied Time Series Analysis, Forecasting and Control I
Fall 2018STAT 849Advanced Statistical Methods
Spring 2018COMPSCI/STAT 471Introduction to Computational Statistics
Fall 2017STAT 701Applied Time Series Analysis, Forecasting and Control I
Fall 2017STAT 849Advanced Statistical Methods

Teaching history may be incomplete. Course pages contain course-specific feedback and citations.

Instructor identity & provenance
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