I'm posting this note in the ASA's Blog Space to share beyond our Section for Statistical Programmers and Analysts (SSPA) ... there's an exciting webinar on R set for next week:
Using R Effectively to Conduct Linear Regression Analyses
Isabella R. Ghement, Ph.D. (Ghement Statistical Consulting Co.)
Wednesday, January 9, 12:00 p.m. - 1:30 p.m. Eastern time
Registration Deadline: Monday, January 7, at noon Eastern time
http://www.amstat.org/sections/sspa/webinarseries.cfm
This webinar demonstrates the effective use of R for performing linear regression analyses, while also emphasizing good practices to be followed when implementing these analyses in R along with the importance of correctly interpreting the results produced by R. Using a real-world data set, webinar participants will learn how to use R to accomplish the following tasks: (1) produce preliminary numerical and graphical summaries of the data, (2) fit a linear model to the data using the lm() function, (3) extract the output produced by the lm() function, (4) conduct inferences and predictions based on a linear regression model with the help of R functions such as confint() and predict(), (5) create visual displays to aid in the presentation of linear regression model results (e.g., effects plots), (6) detect the presence of collinearity among predictor variables included in a linear regression model, (7) construct parsimonious linear regression models via AIC-driven variable selection methods, and (8) check the validity of the assumptions underlying linear regression models through the use of suitable diagnostic plots. After attending this webinar, participants will be able to develop their own R workflow for conducting linear regression analyses based on the R commands and statistical analysis and interpretation practices covered during the webinar.
About the Presenter
Dr. Isabella R. Ghement is the President of Ghement Statistical Consulting Company Ltd. and provides general and specialized statistical consulting to clients from government, industry and academia along with basic and advanced training workshops on the open-source statistical software package R. Isabella holds a Ph.D. in Statistics from the University of British Columbia, where she continues to teach a graduate-level course on regression methodology using R for the Sauder School of Business.