Linear Regression Assignment Review | Statistics for Applied Epidemiology | Tutorial 7

Linear Regression Assignment Review: Interpreting the coefficients, Model Comparison, Interaction Terms, and more;
Intro to Statistics Course: https://bit.ly/2SQOxDH ; More Statistics and R Programming Tutorials: (https://bit.ly/2Fhu9XU)

This video tutorial goes over linear regression assignment, especially model building process and some tips and guidance for the write up portion.

Here we will go over interpretations of coefficients in a linear regression model, nested model comparison, adding interaction terms, hypothesis testing and more.



In this statistics tutorial we will

► Learn to interpret logistic regression output including log odds of an outcome
►Learn how to estimate odds ratio and odds of an outcome
►Discuss the links between odds and probability
► Learn how to identify confounding
► Learn how to assess model fit
► Learn how to identify effect modification/interaction with logistic regression



►► 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



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This statistics video 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!