STAT 436 teaches data visualization techniques within data science workflows, covering data preparation, exploratory analysis, and model interpretability.
The course uses a flipped format with pre-lecture readings, a large group project, and exams. Some students find it easy to succeed with minimal effort, while others note the material requires deep engagement.
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(STAT 240 or 303), graduate professional/standing, or declared in Statistics VISP
This is a best-effort interpretation; check the catalog requirements above.
Kris Sankaran is praised for his clarity, helpfulness, and passion, with clear notes and effective explanations. Reviewers highlight his accessible nature and strong teaching skills. However, one review criticizes his disorganization and fragmented content distribution.
Recent recorded grades — Fall 2024: 3.52 GPA, 71.6% A/AB (n=67 letter grades); Spring 2025: 3.48 GPA, 67.7% A/AB (n=96 letter grades); Fall 2025: 3.53 GPA, 76.1% A/AB (n=92 letter grades). Includes jointly taught sections.
No course-specific feedback yet.
Cameron Jones is a historical instructor for this course. Reviewers describe him as an amazing professor who taught extremely well and made the compacted summer course manageable with lax deadlines. He helped students master R through effort and time investment.
CAMERON JONES is recorded teaching in Spring 2025. Recorded history may be incomplete and does not establish a future schedule.
KRIS SANKARAN is recorded teaching in Spring 2023, Spring 2024, Fall 2024, Spring 2025, Fall 2025. Recorded history may be incomplete and does not establish a future schedule.
Recorded history may be incomplete and does not establish a future schedule.
Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
|---|---|---|---|
| LEC 001 | Classroom Instruction | 93 / 98 | 17 |
| LEC 002 | Classroom Instruction | 1 / 2 | 0 |
Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.
Kris Sankaran is praised for articulating concepts clearly and providing helpful in-class examples. Conversely, one reviewer criticizes him as disorganized and notes the course materials are scattered across multiple files.
Recent recorded grades — Spring 2025: 3.48 GPA, 67.7% A/AB (n=96 letter grades); Fall 2025: 3.53 GPA, 76.1% A/AB (n=92 letter grades); Spring 2026: 3.46 GPA, 75.8% A/AB (n=95 letter grades).
The course uses a flipped format with pre-lecture readings, a large group project, and exams. Some students find it easy to succeed with minimal effort, while others note the material requires deep engagement.
Students value the clear online notes, helpful examples, and development of visualization and writing skills. Conversely, one reviewer found the course structure incohesive and frustrating to navigate.
Latest available · Spring 2026— not enough history to project Fall 2026.
Through Spring 2026
Latest available grades · Spring 2026 · all course levels
GPA
Higher than % of other courses in this group.
Course GPAs · red marks this course’s range
letter grades
More recorded grades than % of other courses in this group.
Typical course in this group: letter grades.
1283 courses over the same term, each with at least 30 recorded letter grades. Cross-listed courses count once. GPA is not a measure of difficulty or teaching quality. The typical course is the median by recorded grade count; tied values are not counted as lower. Grade counts describe course scale, not unique students or typical section size.
Descriptions compare GPA with this group’s average: at least 0.20 higher or lower; otherwise close to average. Section size uses median recorded enrollment: small up to 30, mid-sized 31–99, large 100+. Lectures and discussion/lab sections are described separately.
Descriptions, prerequisites, and recorded course offerings.
Observations at scan time; dates do not imply when a catalog change took effect.
Statistical Data Visualization
Recorded 2026-09-07[
{
"run_id": "20260907T155543-ce3781c4",
"semester": "1272",
"observed_at": "2026-09-07 15:55:43.033547+00:00",
"offering_id": "1272:932:026276",
"course_id": "STAT 436",
"course_uid": "course_f57701752c565e5b0c704a1d",
"term_id": "1272",
"source_course_id": "026276",
"source_subject_id": "932",
"title": "Statistical Data Visualization",
"credits_min": 3,
"credits_max": 3,
"typically_offered": "Not Applicable"
}
]Original comments behind the course and instructor summaries.
Recorded grade distributions by term, section, and instructor.
Explore recorded gradesRecorded model configuration, reasoning, and tool conversations.
{
"model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
"model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
"task_version": "14",
"output_id": "1f96ac792b742f82e85b0ef3a33369de04d4abb1aed4d1287df2361908f0809f",
"requirements_status": "valid",
"dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
"observed_at": "2026-09-07 15:55:43.033547+00:00"
}