Logistic Regression [Simply explained]

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. ► Load Example Dataset https://numiqo.com/statistics-calculator/regression?example=Medical_example_logistic_regression ► Online Logistic Regression Calculator https://numiqo.com/statistics-calculator/regression ►Tutorial Logistic Regression https://numiqo.com/tutorial/logistic-regression ► E-BOOK https://numiqo.com/statistics-book 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) #statistics