Multiple Linear Regression II | Statistics for Applied Epidemiology | Tutorial 3

Multiple Linear Regression II Video Tutorial: Choosing the best model and Fitting a regression model; Linear Regression Concept and with R (https://bit.ly/2z8fXg1) More Statistics and R Programming Tutorials: (https://bit.ly/2Fhu9XU) In this video tutorial, we continue learning about multiple linear regression, and more specifically about confounding, collinearity and effect modification/interaction; we will also discuss how to choosing the best model and then we will go over the steps in fitting a multiple linear regression model ►► Watch More: ► Intro to Statistics Course: https://bit.ly/2SQOxDH ►R Tutorials for Data Science https://bit.ly/1A1Pixc ►Getting Started with R (Series 1): https://bit.ly/2PkTneg ►Graphs and Descriptive Statistics in R (Series 2): https://bit.ly/2PkTneg ►Probability distributions in R (Series 3): https://bit.ly/2AT3wpI ►Bivariate analysis in R (Series 4): https://bit.ly/2SXvcRi ►Linear Regression in R (Series 5): https://bit.ly/1iytAtm ►ANOVA Concept and with R https://bit.ly/2zBwjgL Follow MarinStatsLectures Subscribe: https://goo.gl/4vDQzT website: https://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn This statistics tutorial is prepared to support SPPH 500: Analytic Methods in Applied Epidemiology course offered in the School of Population and Public Health at the University of British Columbia (UBC). These videos are created as part of #marinstatslectures video tutorial series to support some courses at UBC (#IntroductoryStatistics and #RVideoTutorials for Health Science Research), although we make all videos available to the everyone everywhere for free. Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!