Session 1: Wednesday February 25 | Session 2: Thursday February 26 | Session 3: Friday February 27, 2015
This webinar series is the first of two on regression analysis. The second will focus on logistic regression. Participants may register for either or both webinars (a discounted fee applies to those who sign up for both webinar series).
Prior required knowledge
This is a beginner to intermediate level workshop therefore participants will be expected to have some introductory knowledge of hypothesis testing, statistical power, correlation coefficients, and simple bivariate regression. Previous knowledge in and/or work with regression is helpful but not required.
Workshop objectives
By the end of the Linear Regression Webinar Series, participants should be able to:
- Plan for and run linear regression, 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
Instructor
Shayesteh Jahanfor has 21 years of teaching and research experience. She is an analytical consultant, an epidemiologist and a UBC instructor supporting health researchers to gain analytical and study design skills. She is a clinician, has a PhD from New South Wales University, Australia and is currently enrolled to obtain her second PhD at University of British Columbia.
Workshop fees
2 Workshops - Linear and Logistic Regression Webinar Series
- Regular rate: $400
- Graduate rate: $200
1 Workshop – Linear or Logistic Regression Webinar Series
- Regular Rate: $250
Student Rate: $150
Workshop content
Module 1: Part 1 – Linear regression: Identifying and interpreting correlation and regression analysis
Topics covered:
- Interpret scatterplots for quantitative bivariate data
- Identify when to use correlation
- Interpret the results of correlation coefficients
- Identify when to use linear regression
- Assumptions to be met
- How to do the above listed procedures in three software formats: SPSS, SAS, R
Module 1: Part 2 – Linear regression: Interpreting results
Topics covered:
- Interpret the results for linear regression
- Short description of confounder, interaction, covariates
- Multivariate linear analysis
Module 1: Part 3 – Linear regression: Start-to-finish modeling technique
Topics covered:
- Case study: analysing a data set from descriptive statistics to model building
Certificate of workshop completion
All participants will be issued a certificate of workshop completion following a short summary quiz.
