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Binary Logistic Regression with Minitab
Highest Rated
Rating: 4.6 out of 5(90 ratings)
574 students

Binary Logistic Regression with Minitab

Perform and Analyze the Results of Binary Logistic Regression Analysis using Minitab 19
Last updated 9/2021
English

What you'll learn

  • Master Binary Logistic Regression, a crucial classification technique in data science, machine learning, and statistics.
  • Learn to predict binary outcomes (yes/no, true/false, sick/healthy) based on continuous independent variables.
  • Perform and interpret Binary Logistic Regression analysis using Minitab with ease and accuracy.
  • Analyze and interpret the Confusion Matrix to evaluate the performance of your model.
  • Learn to use the Receiver Operating Characteristic (ROC) Curve for assessing model accuracy.
  • Apply your knowledge through project work, such as evaluating the effectiveness of an ad campaign for a new cereal.
  • Build a strong foundation in logistic regression to boost your career in data science, machine learning, and statistical analysis.

Course content

5 sections32 lectures3h 3m total length
  • Introduction - Linear Regression7:58
  • Introduction - Logistic Regression4:00
  • Logistic Regression Results7:58
  • Section 1 Quiz - Introduction to Logistic Regression

Requirements

  • You should have a good understanding of the Linear and Multiple Regression Analysis
  • Else take my Mastering Multiple Regression with Minitab: A Deep Dive course before starting this course.
  • You can download 30 days trial version of Minitab for practice from their website

Description

In this course, I will teach you one of the most commonly used classification techniques in data science, machine learning and statistics and that is: Binary Logistic Regression.

A binomial logistic regression is used to predict the binary output (yes/no, true/false, sick/healthy) based on one or more continuous independent variables. It is often referred to as logistic regression. However, in Minitab, it is called binary logistic regression.

I will use Minitab 19 to perform the analysis. The focus of my teaching will be on explaining the theoretical concepts and on analyzing and interpreting the results of the analysis.

Performing Binary Logistic Regression in Minitab is easy. It is just a few selections and clicks and you are done with it. However, the difficult part is understanding and interpreting the results.

The following concepts are covered in this course:

  • The purpose of Binary Logistic Regression

  • The concept of Odds and ln(Odds)

  • Logistic Regression Equation

  • Odds Ratio

  • Confusion Matrix

  • Receiver Operating Characteristic (ROC) Curve

  • R-Squared in context of Logistic Regression

  • Hosmer-Lemeshow Goodness of Fit Test

  • Project work to practice all the above concepts

In the project work, marketers at a cereal company investigate the effectiveness of an ad campaign for a new cereal. Three factors considered in this project are the income, whether the person has seen the advertisement and whether the person has kids in the house.

Here we performed binary logistic regression to determine whether people who saw the ad are more likely to buy the cereal.

After completing this course, you will be easily able to perform the logistic regression, select the model.

Who this course is for:

  • Six Sigma or Data Analysis professionals who want to take their understanding of Regression Analysis to the next level.
  • Anyone who wants to get a more in-depth insight into interpreting the Logistic Regression results