What is a Logistic Regression? How is it calculated? And most importantly, how are the logistic regression results interpreted? In a logistic regression, the dependent variable is a dichotomous variable. Dichotomous variables are variables with only two values. For example: Whether a person buys or does not buy a particular product. Logistic regression is very often used in machine learning.
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00:00 What is a Regression
00:45 Difference between Linear Regression and Logistic Regression
01:24 Example Logistic Regression
02:23 Why do we need Logistic Regression?
03:31 Logistic Function and the Logistic Regression equation
05:01 How to interpret the results of a Logistic Regression?
07:58 Logistic Regression: Results Table
08:21 Logistic Regression: Classification Table
09:19 Logistic Regression: and Chi Square Test
10:22 Logistic Regression: Model Summary
11:24 Logistic Regression: Coefficient B, Standard error, p-Value and odds Ratio
13:56 ROC Curve (receiver operating characteristic curve)
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