This video describes how to do Logistic Regression in R, step-by-step. We start by importing a dataset and cleaning it up, then we perform logistic regression on a very simple model, followed by a fancy model. Lastly we draw a graph of the predicted probabilities that came from the Logistic Regression.
The code that I use in this video can be found on the StatQuest GitHub:
github.com/StatQuest/logistic...
For more details on what's going on, check out the following StatQuests:
For a general overview of Logistic Regression:
• StatQuest: Logistic Re...
The odds and log(odds), clearly explained:
• Odds and Log(Odds), Cl...
The odds ratio and log(odds ratio), clearly explained:
• Odds Ratios and Log(Od...
Logistic Regression, Details Part 1, Coefficients:
• Logistic Regression De...
Logistic Regression, Details Part 2, Fitting a line with Maximum Likelihood:
• Logistic Regression De...
Logistic Regression Details Part 3, R-squared and its p-value:
• Logistic Regression De...
Saturated Models and Deviance Statistics, Clearly Explained:
• Saturated Models and D...
Deviance Residuals, Clearly Explained:
• Deviance Residuals
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statquest.org/video-index/
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0:00 Awesome song and introduction
0:29 Load and format data
3:54 Dealing with missing data
5:03 Verifying that the data is not imbalanced
6:44 Logistic regression with one independent variable
12:48 Logistic regression with many independent variables
15:13 Graphing the predicted probabilities
#statquest #logistic
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