Linear and Logistic Regression
Linear Regression: Learn how to:
- Plan for and run linear regression in SPSS, checking statistical assumptions and appropriateness of the regression results including being aware of the common misconceptions and hazards in interpreting regression results.
- Communicate effectively with statistical analysis on regression methods
- Understand the concepts such as covariate, confounder and interactions
- Work on a data set to produce tangible results to build a parsimonious model starting from descriptive analysis to model fitting
Logistic Regression: Learn how to:
- Identify the circumstances and situations in which logistic regression is appropriate, if not required
- Understand and interpret logistic regression output from commonly used software such as SPSS.
6 x 2 hour sessions, 10am – 12pm
Starts May 9
Prerequisites: This is a beginner to intermediate level webinar series. Some introductory knowledge of hypothesis testing, statistical power, correlation coefficients, and simple bivariate regression. Previous knowledge of regression is not required.
Latent Growth Modeling
Focuses on the practical application of structural equation modeling for analysis of longitudinal data with specific applications for social and health researchers.
5 day workshop
starts May 9
Pop Data BC’s Education & Training Unit also offers:
|Professional Specialization Certificate in Population Health Data Analysis|