Historical instructor

YIWEI ZHANG

Adjusted rating
RMP difficulty
captured reviews
About this rating

Raw average: 4.25/5 from 4 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

CNSRSCI 301
Quality 5/5Difficulty 4/5
She teaches statistics better than some professors in the stats department. Exams are hard but you learn a lot from them. If you like analytics and don't mind 8 am this is a great class.
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CNSR301 · course not matched
Quality 5/5Difficulty 3/5
She is amazing! This semester, this course is entirely online, but the course is still run really well. Even if you haven't taken a stats class before, this course is totally doable. Her examples and her lectures are great, and I found this course to be very interesting. Overall, not too much work, and I would recommend this course to anyone.
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CNSRCI301 · course not matched
Quality 2/5Difficulty 3/5
New teacher in Madison, almost felt as though she was too smart to teach excel. She moved pretty quick sometimes so it can be hard to keep up when she's doing demonstrations with excel, sometimes it was just better to watch and absorb. First half of the course is in excel, the other half is interpreting store data and doing presentations
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CNSRSCI 301
Quality 5/5Difficulty 4/5
(I think) It was Professor Zhang's first semester at UW and she did such a great job! I was dreading this course, but the professor made the material easier to understand, and provided a lot of resources (videos, powerpoints, etc) to use outside of class to help. 3 group projects, but she provided great feedback so we could improve every time!
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Personal experiences, not a representative survey. Profile matching and captured coverage are shown in the source details.

Classes with YIWEI ZHANG

CNSRSCI 301

Consumer Analytics

3 credits

Consumer Analytics teaches leveraging data analysis to drive business decisions through evidence-based storytelling.

No offering record · Spring 2026

with this instructor · course overall, matching historical terms

Yiwei ZhangGisella Kagy+1 more

historical GPA · grades

Fall 2021–Spring 2026
CNSRSCI 778

Causal Models in Household and Consumer Research

Credits unavailable

Research on applying modern econometric techniques for causal inference in empirical consumer research.

No offering record · Spring 2026

with this instructor · course overall, matching historical terms

Yiwei Zhang

historical GPA · grades

Spring 2025–Spring 2026 · limited sample

Recorded teaching history

Distinct courses recorded per term

Explore courses taught by this instructor →
Browse recorded courses
TermCourseTitle
Spring 2026CNSRSCI 301Consumer Analytics
Spring 2026CNSRSCI 778Causal Models in Household and Consumer Research
Spring 2026CNSRSCI 990Research and Thesis
Fall 2025CNSRSCI 301Consumer Analytics
Fall 2025CNSRSCI 852Advanced Consumer Policy
Fall 2025CNSRSCI 990Research and Thesis
Spring 2025CNSRSCI 301Consumer Analytics
Spring 2025CNSRSCI 778Causal Models in Household and Consumer Research
Spring 2025CNSRSCI 990Research and Thesis
Spring 2025CNSRSCI 999Independent Study
Fall 2024CNSRSCI 301Consumer Analytics
Fall 2024CNSRSCI 999Independent Study
Spring 2024CNSRSCI 901Graduate Special Topics in Consumer Science
Spring 2024CNSRSCI 990Research and Thesis
Spring 2024CNSRSCI 999Independent Study
Fall 2023CNSRSCI 301Consumer Analytics
Fall 2023CNSRSCI 990Research and Thesis
Fall 2023CNSRSCI 999Independent Study
Spring 2023CNSRSCI 990Research and Thesis
Spring 2022CNSRSCI 901Graduate Special Topics in Consumer Science
Fall 2021CNSRSCI 301Consumer Analytics
Fall 2020CNSRSCI 301Consumer Analytics
Fall 2020CNSRSCI 999Independent Study
Spring 2020CNSRSCI 901Graduate Special Topics in Consumer Science
Fall 2019CNSRSCI 301Consumer Analytics

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

Instructor identity & provenance 
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