Carnegie Mellon University

Statistics – Neuroscience Track

New technologies for measuring the brain are revolutionizing our understanding of the brain, and the revolution is data-driven.

This track focuses on the statistical problems in neuroscience, including neural data analysis and neuroimaging. It is ideal for students interested in data science with an emphasis on brain and behavior or in neuroscience with an emphasis on data analysis.

Contact the Statistics & Data Science Academic Advisors

Statistics and Neuroscience Track

Theory Requirements

Course Topic/Title Course Number Units Prerequisites
Calculus 21-111 and 112, or 21-120 20 or 10
Multivariate 21-256, 21-259, or 21-268  9–10 21-112 or 21-120
Linear/Matrix Algebra 21-240, 21-241, or 21-242 10
Probability 36-225, 36-218, 36-219, 21-325, or 15-359  9 various
Statistical Inference 36-226 or 36-326  9 C or higher in 36-225, 36-218, 36-219, 21-325, or 15-359

Data-Analysis Requirements

Course Topic/Title Course Number Units Prerequisites
Beginning Data Analysis 36-200  9
Intermediate Data Analysis 36-202, 36-208, 36-290, or 36-309  9
Advanced Elective 36-303, 36-311, 36-315, 36-318, 36-46x, or 36-490, 36-493 or 36-497  9 36-202, 36-208, 36-290, or 36-309
Special Topics 36-46x  9 various
Modern Regression 36-401  9 C or higher in 36-226, 36-326, or 36-625 and pass (21-240 or 21-241) and (21-256 or 21-259 or 21-268)
Advanced Methods for Data Analysis 36-402  9 C or higher in 36-401
Computing Requirements
Course Topic/Title Course Number Units Prerequisites
Statistical Computing 36-350 or 36-650  9 (36-202 or 36-208 or 36-309 or 70-208, or 36-290 or equivalent) and 36-225

Neuroscience Requirements

Course Topic/Title Course Number Units Prerequisites
Cognitive Psychology 85-211  9
Biological Foundations of Behavior 85-219  9 85-100 or instructor approval
Three Neuroscience Electives

With at least one selected from each list
(A) Methodology and Analysis and
(B) Neuroscientific Background.

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List of Approved Neuroscience Electives A: Methodology and Analysis

Course Topic/Title Course Number Units Prerequisites
Probability and Mathematical Statistics or Intermediate Statistics 36-700 or 36-705 12
Machine Learning 10-301 12 15-122 and (15-151 or 21-127)
Systems Neuroscience 18-290 12 18-100
Cognitive Science Research Methods 85-314 12 36-309
Neural Data Analysis 86-631 or 42-631 12

List of Approved Neuroscience Electives B: Neuroscientific Background

Course Topic/Title Course Number Units Prerequisites
Cellular Neuroscience 03-362  9 85-219, 42-202, 03-161, or 03-240
Systems Neuroscience 03-363  9 85-219, 42-202, 03-161, or 03-240
Neural Computation 15-386  9 21-122 and 15-122
Cognitive Neuropsychology 85-414  9 85-219 or 85-211
Intro to Parallel Distributed Processing 85-419  9 85-213 or 85-211