Course Material

Online notes

Online Course Delivery

We have switched to a completely online course delivery system

Course notes are available through this site via the Course Material tab
Homework assignments are available through the Homework Assignments tab, and also Moodle. HW submissions are via Moodle.
There will be no in-person lectures. Lectures will be pre-recorded and will be available via Mediasite.
Office hours for Dr. Maity will be held by Zoom. The new office hours are Friday from 4:00 pm to 6:00 pm. You can join using the link https://ncsu.zoom.us/j/8308506877 or using the meeting id 830-850-6877.
TA office hours are unchanged — Monday 10a – 11:30a and Tuesday 1p – 2:30p, and will be held via Zoom. You can join using the link https://ncsu.zoom.us/j/6327193110 or using the meeting id 632-719-3110.

Recorded lectures are available via mediasite

Multivariate Data Analysis
Introduction
Vectors and Matrices using R
Multivariate Summary Statistics
Multivariate Normal Distribution	Lumber stiffness data [Table 4.3 in Johnson and Wichern (2007)] used on page 9. The first four columns are the four measures of stiffness (x1 — x4); the last column is the Mahalanobis distance (d2).
Inference about a mean vector
Comparison of several mean vectors – Part I Comparison of several mean vectors – Part II	Wastewater monitoring data [Table 6.1 of Johnson and Wichern (2007)] used in the paired comparison. Dog anesthesia data [Table 6.2 in Johnson and Wichern (2007)] used in multiple treatments comparison. Lizard data [Table 6.7 of Johnson and Wichern (2007)] used in the two-sample analysis.
Principal Components Analysis	Stock price data [Table 8.4 of Johnson and Wichern (2007)]
Factor Analysis	Hemangioma data [Table 8.2 of Applied Multivariate Statistics with R by Daniel Zelterman]
Discriminant Analysis and Classification	Wines data [https://archive.ics.uci.edu/ml/datasets/wine; also available with the book Applied Multivariate Statistics with R by Zelterman]
Longitudinal Data Analysis
Introduction	TLC data [Details at https://content.sph.harvard.edu/fitzmaur/ala2e/] Six cities FEV1 data [Details at https://content.sph.harvard.edu/fitzmaur/ala2e/]
March 24th and 26th: see mediasite videos here (video name: ST 437- 537 001 SPRG 2020_3/17/2020) and here (video name: ST 437- 537 001 SPRG 2020_3/19/2020). We cover the entire lecture “Models for mean and covariance” and first five(5) pages of “Estimation in the General Linear Model” posted below.
Models for mean and covariance	Ultrafiltration Data used in Example B. Hip replacement data used in Example C.
Estimation in the General Linear Model March 31st and April 2nd: see mediasite videos in Wolfware/Moodle. We cover pages 6 — 22 of “Estimation in the General Linear Model”.	The Vlagtwedde-Vlaardingen Study data used as an example. [Details at https://content.sph.harvard.edu/fitzmaur/ala2e/]
Linear Mixed Effects Models (to be updated) April 4 (makeup day) and April 7: see mediasite videos in Wolfware/Moodle. We cover pages 23 to end of “Estimation in the General Linear Model” and pages 1 — 7 of “Linear Mixed Effects Model”. April 9: see mediasite video in Wolfware/Moodle. We cover pages 8 — 15 of “Linear Mixed Effects Model”.