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
STAT260
Introduction to Probability and Statistics I
Descriptive statistics; elementary probability theory; random variables, discrete and continuous probability distributions, expectation, joint, marginal and conditional distributions; linear functions of random variables; random sampling and sampling distributions; point and interval estimation; classical hypothesis testing and significance testing. The mathematical foundations of statistical inference are introduced and illustrated with examples from a variety of disciplines.
Lecture: 3h
Lab: 0h
Tutorial: 0h
Credits: 1.5