Poisson Regression Part I | Statistics for Applied Epidemiology | Tutorial 9

Poisson Regression: Why do we use Poisson Regression, How to fit a Poisson Regression model and more!
Intro to Statistics Course: https://bit.ly/2SQOxDH ; More Statistics and R Programming Tutorials: (https://bit.ly/2Fhu9XU)

After watching this statistics tutorial, you would be able to…

►Understand why/when we use a Poisson regression model
►Understand events, counts, incidence, rates
►Fit a Poisson regression model,
►interpret output of a Poisson regression model
●Check for confounding, effect modification
●Compare nested models


►► 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

Content Creator and Producer: Mary Clare Kennedy (M.A.), Research Associate at UBC


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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!