MAT 3375 Regression Analysis

3 units
Mathematics
Faculty of Science
Modeling relationships between outcome (dependent) variables and covariates (independent variables) using simple and multiple linear regression models. Estimation and hypothesis testing using least squares and likelihood methods. Performing model diagnostics and assessing goodness of fit properties. Variable selection and finding the best fit. Non-linear regression and transformations. Weighted regression and generalized least square. Analysis of data using statistical software packages.

Components:

Laboratory
Lecture

Requirements:

Prerequisites: MAT 1341 , MAT 2371 , ( MAT 2375 or MAT 2378 or MAT 2379 ).

Previously Offered Terms:

Fall
Summer

French Equivalent:

All Professors
B Average (5.877)
Most Common: A+ (15%)
544 students

P

S

NS

F

D

C

B

A-

A+

Youssouph Cissokho

Summer 2024 - X00

B Average (5.795)
Most Common: A (26%)
39 students

P

S

NS

F

D

C

B

A-

A+

Mayer Alvo

2 sections from Fall 2019 to Fall 2023

B+ Average (6.645)
Most Common: A (24%)
141 students

P

S

NS

F

D

C

B

A-

A+

Patrick Boily

Summer 2023 - X00

B Average (5.744)
Most Common: B (22%)
78 students

P

S

NS

F

D

C

B

A-

A+

Jemila Seid Hamid

Fall 2022 - A00

C+ Average (4.703)
Most Common: F (14%)
118 students

P

S

NS

F

D

C

B

A-

A+

Gilles Lamothe

Summer 2019 - X00

B Average (6.179)
Most Common: A+ (16%)
56 students

P

S

NS

F

D

C

B

A-

A+

Mahmoud Zarepour

Fall 2018 - A00

C Average (3.964)
Most Common: F (18%)
55 students

P

S

NS

F

D

C

B

A-

A+

Termeh Kousha

Fall 2017 - A00

A- Average (8.193)
Most Common: A+ (47%)
57 students

P

S

NS

F

D

C

B

A-

A+