Free Udemy Courses

Six Sigma Black Belt Level Regression Analysis – Free Udemy Courses

Six Sigma Black Belt Level Regression Analysis - Free Udemy Courses
Six Sigma Black Belt Level Regression Analysis - Free Udemy Courses

Six Sigma Black Belt Level Regression Analysis – Free Udemy Courses

Get ready for ASQ & IASSC Six Sigma Black Belt Certification BoK Topic | Get a Primer on Predictive Modeling

What you’ll learn

Six Sigma Black Belt Level Regression Analysis – Free Udemy Courses

  • Build Predictive Models based on Multiple Linear and Logistic Regression
  • Analyze and Interpret results of Regression Models

Requirements

  • Real Life Scenario Based Exposure to the following tools and concepts
  • Scatter Diagrams, Correlation, Co-correlation & Multicollinearity
  • Multiple Linear Regression – Line of Best Fit, Least Sq Method, Best Sub-set Metho
  • Logistic Regression using Logit Function
  • Residual Analysis
  • Terms such as Pearson’s Correlation, Spearman’s Rho, VIF, R-sq, R-sq (adj), R-sq (pred), S Value, Mallow’s Cp
  • Confidence Band and Prediction Band

Description

If you are a Six Sigma Black Belt Aspirant or simply a Six Sigma Aspirant, you will find this course of real help. Here’s why: Regression Analysis is a topic of importance in ASQ and IASSC Certification Tests. With this course, you will be able to answer quite a few questions and easily add a few marks. That’s guaranteed!

If you are a machine learning enthusiast, then you already know that one of the foundation pillars of Machine Learning & Predictive Modeling is Statistical Modeling (& Regression Analysis). If you don’t have a formal education in statistics or modeling but have a strong programming background, this course will serve as a primer, explaining the concepts, (without coding).

Of course, in Machine Learning some other models & algorithms are not in the scope of this course.

What are you going to get:

  • Correlation & Scatter Diagram
  • Single Linear Regression using Line of Best Fit
  • Multiple Linear Regression with Best sub-set method
  • Residual Analysis
  • Various Statistics: R-sq, R-sq(Adj), R-sq(Pred), S Value, Mallow’s Cp, VIF
  • Multi-collinearity
  • Spearman’s Coefficient
  • Logistic Regression using the Logit function
  • Predictive Analytics

Who this course is for:

  • Six Sigma Black Belt Aspirants
  • Six Sigma Aspirants, in general
  • Machine Learning & Statistical Modeling Enthusiasts
Udemy Free Courses Get Course Now
Tags



Categories



Categories






Categories