Binary Logistic Regression with Minitab
What you'll learn
- Mastering Binary Logistic Regression
- Perform and interpret the results of Logistic Regression Analysis using Minitab
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
Course content
- Preview07:58
- Preview04:00
- 07:58Logistic Regression Results
- 2 questionsSection 1 Quiz - Introduction to Logistic Regression
Instructor
![Sandeep Kumar ](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.5 Instructor Rating
- 30,285 Reviews
- 147,201 Students
- 25 Courses
PMI-PMP, IRCA Registered Lead Auditor, ASQ - CSSBB, CQA, CQE, CMQ/OE, IIA - CIA
Sandeep Kumar has more than 35 years of Quality Management experience. He has worked as Quality Manager/Director on a number of projects, including Power, Oil and Gas and Infrastructure projects.
In addition, he provides consulting services to implement Lean Six Sigma to improve performance.
His areas of specialization include Quality Assurance, ISO 9001:2015, Lean, Six Sigma, Risk Management, QMS Audits, Supplier Quality Surveillance, Supplier Pre-qualification, Construction Quality, Mechanical Inspection and Quality Training.
Professional Qualifications:
His professional qualification/certifications include:
• ASQ-CSSBB, Certified Six Sigma Black Belt
• ASQ-CMQ/OE Certified Manager of Quality/Organizational Excellence
• PMI-PMP Certified Project Management Professional
• IRCA Registered Lead Auditor (QMS-2015)
• IIA-CIA Certified Internal Auditor
• ASQ-CSSGB, Certified Six Sigma Green Belt
• ASQ-CQA Certified Quality Auditor
• ASQ-CQE Certified Quality Engineer