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5 course outlines found

1

STATS 331

: Introduction to Bayesian Statistics
2024 Semester Two (1245)
Introduces Bayesian data analysis using the WinBUGS software package and R. Topics include the Bayesian paradigm, hypothesis testing, point and interval estimates, graphical models, simulation and Bayesian inference, diagnosing MCMC, model checking and selection, ANOVA, regression, GLMs, hierarchical models and time series. Classical and Bayesian methods and interpretations are compared.
Subject: Statistics
Prerequisite: ENGSCI 314 or STATS 201 or 208
2

STATS 331

: Introduction to Bayesian Statistics
2023 Semester Two (1235)
Introduces Bayesian data analysis using the WinBUGS software package and R. Topics include the Bayesian paradigm, hypothesis testing, point and interval estimates, graphical models, simulation and Bayesian inference, diagnosing MCMC, model checking and selection, ANOVA, regression, GLMs, hierarchical models and time series. Classical and Bayesian methods and interpretations are compared.
Subject: Statistics
Prerequisite: ENGSCI 314 or STATS 201 or 208
3

STATS 331

: Introduction to Bayesian Statistics
2022 Semester Two (1225)
Introduces Bayesian data analysis using the WinBUGS software package and R. Topics include the Bayesian paradigm, hypothesis testing, point and interval estimates, graphical models, simulation and Bayesian inference, diagnosing MCMC, model checking and selection, ANOVA, regression, GLMs, hierarchical models and time series. Classical and Bayesian methods and interpretations are compared.
Subject: Statistics
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209
4

STATS 331

: Introduction to Bayesian Statistics
2021 Semester Two (1215)
Introduces Bayesian data analysis using the WinBUGS software package and R. Topics include the Bayesian paradigm, hypothesis testing, point and interval estimates, graphical models, simulation and Bayesian inference, diagnosing MCMC, model checking and selection, ANOVA, regression, GLMs, hierarchical models and time series. Classical and Bayesian methods and interpretations are compared.
Subject: Statistics
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209
5

STATS 331

: Introduction to Bayesian Statistics
2020 Semester Two (1205)
Introduces Bayesian data analysis using the WinBUGS software package and R. Topics include the Bayesian paradigm, hypothesis testing, point and interval estimates, graphical models, simulation and Bayesian inference, diagnosing MCMC, model checking and selection, ANOVA, regression, GLMs, hierarchical models and time series. Classical and Bayesian methods and interpretations are compared.
Subject: Statistics
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209