Exploring term Fall 2023 Change
- ACAN: Arts of Canada
 - ADMN: Public Administration
 - AE: Art Education
 - AGEI: Ageing
 - AHVS: Art History and Visual Studies
 - ANTH: Anthropology
 - ART: Visual Arts
 - ARTS: Arts
 - ASL: American Sign Language
 - ASTR: Astronomy
 - ATWP: Academic and Technical Writing Program
 - BCMB: Biochemistry and Microbiology
 - BIOC: Biochemistry
 - BIOL: Biology
 - BME: Biomedical Engineering
 - CE: Community Engagement
 - CHEM: Chemistry
 - CIVE: Civil Engineering
 - COM: Commerce
 - CS: Canadian Studies
 - CSC: Computer Science
 - CW: Creative Writing (En'owkin Centre)
 - CYC: Child and Youth Care
 - DHUM: Digital Humanities
 - DSST: Disability Studies (DSS)
 - ECE: Electrical and Computer Engineering
 - ECON: Economics
 - ED-D: Educational Psychology and Leadership Studies
 - ED-P: Curriculum and Instruction Studies
 - EDCI: Curriculum and Instruction Studies
 - EDUC: Education
 - ENGR: Engineering
 - ENSH: English
 - ENT: Entrepreneurship
 - EOS: Earth and Ocean Sciences
 - EPHE: Exercise Science, Physical and Health Education
 - ER: Environmental Restoration
 - ES: Environmental Studies
 - EUS: European Studies
 - FA: Fine Arts
 - FRAN: French and Francophone Studies
 - GDS: Global Development Studies
 - GEOG: Geography
 - GMST: Germanic Studies
 - GNDR: Gender Studies
 - GREE: Greek
 - GRS: Greek and Roman Studies
 - HDCC: Human Dimensions of Climate Change
 - HINF: Health Information Science
 - HLTH: Health
 - HS: Health and Society
 - HSD: Human and Social Development
 - HSTR: History
 - HUMA: Humanities
 - IB: International Business
 - ICDG: Indigenous Community Development and Governance
 - IED: Indigenous Education
 - IGOV: Indigenous Governance
 - INGH: Indigenous Health Studies
 - INTS: International Health Studies
 - IS: Indigenous Studies
 - ISP: Intercultural Studies and Practice
 - ITAL: Italian
 - LAS: Latin American Studies
 - LATI: Latin
 - LAW: Law
 - LING: Linguistics
 - MATH: Mathematics
 - MDIA: Media Studies
 - MECH: Mechanical Engineering
 - MEDI: Medieval Studies
 - MEDS: Medical Science
 - MICR: Microbiology
 - MRNE: Marine Science
 - MUS: Music
 - NURS: Nursing
 - PAAS: Pacific and Asian Studies
 - PHIL: Philosophy
 - PHYS: Physics
 - POLI: Political Science
 - PORT: Portuguese
 - PSYC: Psychology
 - RCS: Religion, Culture and Society
 - SCIE: Science
 - SENG: Software Engineering
 - SJS: Social Justice Studies
 - SLST: Slavic Studies
 - SMGT: Service Management
 - SOCI: Sociology
 - SOCW: Social Work
 - SOSC: Social Science
 - SPAN: Spanish
 - STAT: Statistics
 - TCA: Transformative Climate Action
 - THEA: Theatre
 - TS: Technology and Society
 - VIRS: Visiting International Research Studies
 - VKUR: Valerie Kuehne Undergraduate Research Award
 - WRIT: Writing
 
- STAT123: Data Science
 - STAT252: Statistics for Business
 - STAT254: Probability and Statistics for Engineers
 - STAT255: Statistics for Life Sciences I
 - STAT256: Statistics for Life Sciences II
 - STAT260: Introduction to Probability and Statistics I
 - STAT261: Introduction to Probability and Statistics II
 - STAT321: Data Management and Presentation
 - STAT350: Mathematical Statistics I
 - STAT353: Applied Regression Analysis
 - STAT354: Sampling Techniques
 - STAT355: Statistical Methods in Health Sciences
 - STAT359: Data Analysis
 - STAT450: Mathematical Statistics II
 - STAT453: The Design and Analysis of Experiments
 - STAT454: Topics in Applied Statistics
 - STAT455: Distribution-Free Statistics
 - STAT456: Multivariate Analysis
 - STAT457: Time Series Analysis
 - STAT458: Generalized Linear Models
 - STAT459: Survival Analysis
 - STAT460: Bayesian Statistics
 - STAT464: Statistical Computing
 - STAT465: Statistical Methods for Genomic Data
 - STAT466: Robust Statistics
 - STAT469: Machine Learning
 - STAT498: Seminar and Independent Project
 
STAT353
Applied Regression Analysis
An outline of linear regression theory with applications; multiple linear regression, polynomial regression, model adequacy checking, variable transformation, variable selection, indicator variable, diagnostics for leverage and influential observations, multicollinearity problem, model selection, stepwise regression, prediction and inference
Lecture: 3h
Lab: 0h
Tutorial: 0h
Credits: 1.5