MATH4465 · Mathematics
Morrissey College of Arts & Sciences
In this course, we will explore various popular statistical methods used in data science. The course will be both theoretical (mathematical) and applied (data- analytic). The mathematical theorems and proofs are an essential part of the course. Part I: Standard Advanced Statistics topicsBayesian Analysis, Analysis of Variance, Bootstrap (Parametric and Non-Parametric), Generalized Linear Regressions, Generalized additive model etc.Part II: Statistical Methods for the 21st century data analysis Principal Component Analysis, Large Scale Hypothesis Testing, Ridge and Lasso Regressions, Random Forest, Support Vector Machines etc.
Course experience
Averages use the original five-point historical evaluation scale.
Organization
4.8 / 5
How well the course was organized
Challenge
4.7 / 5
How intellectually challenging students found it
Attendance
4.8 / 5
How necessary attendance was
Assignments
4.7 / 5
How helpful assignments were
Weekly effort
~5
hours per week
Estimated from the original workload response buckets. Individual sections may differ.
Instructor options
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Across time
Section-level results available in the recovered archive.
Spring 2025
1 section