MAT 3379 Introduction to Time Series Analysis

3 units
Mathematics
Faculty of Science
Time domain methods: detrending, dealing with non stationarity and seasonality; autoregressive moving average (ARMA) models: forecasting, estimation, diagnostics. Selected topics from: state space methodology, financial time series, time series regression, spectral domain. Time series data will be analyzed using software packages.

Components:

Laboratory
Lecture

Requirements:

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

Previously Offered Terms:

Winter
Summer

French Equivalent:

MAT 3779
GradesEvaluations
All Professors
B Average (6.481)
Most Common: A+ (28%)
534 students

P

S

NS

F

D

C

B

A-

A+

Mahmoud Zarepour

5 sections from Winter 2018 to Winter 2025

C+ Average (4.822)
Most Common: A+ (13%)
230 students

P

S

NS

F

D

C

B

A-

A+

Youssouph Cissokho

3 sections during Winter 2025

No grade data available for this course.

Rafal Kulik

Winter 2024 - A00

A- Average (7.939)
Most Common: A+ (43%)
115 students

P

S

NS

F

D

C

B

A-

A+

Hai Yan Liu

Summer 2022 - X00

B+ Average (7.257)
Most Common: A+ (29%)
70 students

P

S

NS

F

D

C

B

A-

A+

Unknown Professor

Winter 2022 - A00

A- Average (7.824)
Most Common: A+ (43%)
119 students

P

S

NS

F

D

C

B

A-

A+