Statistical Methods for Research 2

Statistical Methods for Research 2
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.
 Hours3.0 Credit, 3.0 Lecture, 2.0 Lab
 PrerequisitesSTAT 511
 ProgramsContaining STAT 512
Course Outcomes: 


Fit a two-way ANOVA and interpret the main effects and interaction

Fixed and Random Effects

Explain the differences between fixed and random effects and interpret computer output from mixed model analyses

Evidence of Autocorrelation

Identify evidence of autocorrelation and fit an ar(1) model to analyze continuous time series data

Multivariate Data

Recognize multivariate data, and appropriately carry out principal components analysis and canoncial correlation analysis using statistical software

Interpret and Calculate

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

Assess Associations

Use X^2 tests and Fisher's Exact tests to assess associations in 2x2 contingency tables

Fit and Interpret

Fit and interpret simple generalized linear regression models (binary response data and count response data) and draw appropriate conclusions justified by the study design

Construct Designs

Construct a factorial design and a screening design