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Correlation & Regression Concepts With Illustrative Example

      Author: Baturi   |   02 February 2023   |   comments: 0

Correlation & Regression Concepts With Illustrative Example
Last updated 10/2021
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.51 GB | Duration: 3h 24m
Correlation and Regression: Types and detailed illustration with example for each type


What you'll learn
Correlation Analysis
Regression Analysis
Types of Correlation and Regression Analysis
Correlation and Regression Analysis using Microsoft Excel
Regression Analysis using Minitab software
Multiple Regression with Practical Examples
Best Subsets Regression with Practical Examples
Requirements
Able to understand English
Description
This course is prepared to understand two important concepts in statistics as well as Six Sigma i.e. Correlation and Regression.This course has 05 sections.Section-1: This consists of-CorrelationCorrelation AnalysisCalculating Correlation CoefficientPractical use of Correlation and Regression with a practical exampleRegressionSignificance F and p-valuesCoefficientsResidual and ConclusionSection-2: This consists of-Regression AnalysisPractical use of each Regression Analysis with ExampleUse of Minitab to conduct Regression AnalysisInterpretation of ResultsSection-3: This consists of-Types and Illustration of each type with a practical exampleNonlinear Regression Analysis1) What are Regression analyses and their types? 2) Brief explanation of all types of Regression Analysis methods3) When to use Nonlinear Regression Analysis?4) Data considerations for Nonlinear Regression5) Nonlinear Regression Analysis with Practical Example in Microsoft Excel6) Interpretation of results from Regression analysis including R-Square, Significance F and p-values, Coefficients, Residuals and Best Fit Model for Nonlinear RegressionLogistic Regression AnalysisBinary Logistic Regression1) What is Binary Logistic Regression Analysis?2) Data considerations for Binary Logistic Regression 3) Detailed Illustration of Binary Logistic Regression Analysis with Practical Example4) Detailed Procedure for Analysis in Minitab5) Interpretation of Results in Session Window6) Interpretation of Results in Graph WindowSection-4: This consists of-Best subset regression with the help of a practical exampleWhat is the Best Subsets Regression?Best Subsets Regression with Practical Example in MinitabDetailed interpretation of results from Best Subsets RegressionMultiple Regression with the help of a practical exampleHow to perform Multiple Regression Analysis in Minitab?Practical Example of Multiple RegressionDetailed interpretation of results in the session window, andDetailed interpretation of results in the graph window.Section-5: This consists of-Quiz to understand and demonstrate understanding of concepts learned in this course.I am sure you will be liked it...
Overview
Section 1: Scatter Diagram: Detailed Illustration with Practical Examples
Lecture 1 Scatter Diagram: Detailed Illustration with Practical Examples
Section 2: Detailed Illustration of "Correlation and Regression Concepts" with example
Lecture 2 Correlation & Regression: Concepts with Illustrative examples
Section 3: Regression Analysis: Types and Illustration of each type with practical example
Lecture 3 Regression Analysis: Types and Nonlinear Regression Analysis
Lecture 4 Nonlinear Regression Analysis: Illustration with Practical Example in Minitab
Lecture 5 Logistic Regression Analysis: Introduction, Types and Data Considerations
Lecture 6 Binary Logistic Regression: Detailed Illustration with Practical Example
Section 4: Multiple Regression: Detailed illustration with Practical Example in Minitab
Lecture 7 Multiple Regression (PART-1): Best Subsets Regression with Practical Example
Lecture 8 Multiple Regression (PART-2): Detailed illustration with Example in Minitab
Section 5: Perform Correlation and Regression In Excel
Lecture 9 Perform Correlation and Regression In Excel
Section 6: Quiz
Students,Professionals,Company Employees,Professors,Entrepreneurs,Suppliers,Customers,Technical People,Managers


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