This video connects back to material learned in intro stats. It begins with a reminder of how we can calculate a sample proportion, and calculate a confidence interval for it. Then how we learn about the Binomial distribution, where we assume we "know" p, the population proportion. It then talks about how in reality we don't know p, and must estimate it, and also that p depends on many other things... and that is where logistic regression comes in...to estimate p as a function of other variables.
The video also talks about how we can use logistic regression to statistically "adjust" an odds ratio (OR) for confounders, etc.
The goal of this video is to connect back to previously learned ideas, and how they are used in logistic regression.
These videos support a course I teach at The University of British Columbia (SPPH 500), which covers the use of regression models in Health Research. These videos were put together to use for remote teaching in response to COVID.
►► Watch More:
► Statistics Course for Data Science https://bit.ly/2SQOxDH
►R Course for Beginners: https://bit.ly/1A1Pixc
►Getting Started with R using R Studio (Series 1): https://bit.ly/2PkTneg
►Graphs and Descriptive Statistics in R using R Studio (Series 2): https://bit.ly/2PkTneg
►Probability distributions in R using R Studio (Series 3): https://bit.ly/2AT3wpI
►Bivariate analysis in R using R Studio (Series 4): https://bit.ly/2SXvcRi
►Linear Regression in R using R Studio (Series 5): https://bit.ly/1iytAtm
►ANOVA Statistics and ANOVA with R using R Studio : https://bit.ly/2zBwjgL
►Hypothesis Testing Videos: https://bit.ly/2Ff3J9e
►Linear Regression Statistics and Linear Regression with R : https://bit.ly/2z8fXg1
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Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC.
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These videos are created by #marinstatslectures to support some statistics courses at the University of British Columbia (UBC) (#IntroductoryStatistics and #RVideoTutorials ), 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!
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