STAT 512
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Statistical Methods for Research 2
Statistics
College of Computational, Mathematical & Physical Sciences
Course Description
Advanced statistical methodologies and experimental design. Topics include multi-way analysis of variance, mixed models analysis of variance, logistic regression, log-linear models, time series models, principal components, canonical correlation, common experimental designs.
When Taught
Winter
Min
3
Fixed/Max
3
Fixed
3
Fixed
2
Note
Lab optional.
Title
Two-Way ANOVA
Learning Outcome
Fit a two-way ANOVA and interpret the main effects and interaction
Title
Fixed and Random Effects
Learning Outcome
Explain the differences between fixed and random effects and interpret computer output from mixed model analyses
Title
Construct Designs
Learning Outcome
Construct a factorial design and a screening design
Title
Interpret and Calculate
Learning Outcome
Interpret and calculate odds, odds ratios, risk differences, and relative risks from 2x2 contingency tables and describe which measures are justified in prospective and retrospective studies
Title
Multivariate Data
Learning Outcome
Recognize multivariate data, and appropriately carry out principal components analysis and canoncial correlation analysis using statistical software
Title
Assess Associations
Learning Outcome
Use X^2 tests and Fisher's Exact tests to assess associations in 2x2 contingency tables
Title
Fit and Interpret
Learning Outcome
Fit and interpret simple generalized linear regression models (binary response data and count response data) and draw appropriate conclusions justified by the study design
Title
Evidence of Autocorrelation
Learning Outcome
Identify evidence of autocorrelation and fit an ar(1) model to analyze continuous time series data
