Correlation & Regression: Concepts with Illustrative example
3.5 (4 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
16 students enrolled

Correlation & Regression: Concepts with Illustrative example

Correlation and Regression: Types and detailed illustration with example for each type
3.5 (4 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
16 students enrolled
Created by Vijay Sabale
Last updated 5/2020
English
Current price: $13.99 Original price: $19.99 Discount: 30% off
5 hours left at this price!
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This course includes
  • 1 hour on-demand video
  • 6 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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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
Course content
Expand all 6 lectures 50:59
+ Scatter Diagram: Detailed Illustration with Practical Examples
1 lecture 05:46

Hello Friends,

In this video, I have explained the basic Quality Control tool i.e. SCATTER DIAGRAM in very detail. Before going to Correlation and Regression, this is a basic topic we must know.

I have tried to explain these tools with the help of practical examples which will be very easy to understand. I have also explained considerations in Scatter diagram and procedure about how to create a Scatter diagram in Microsoft Excel as well as in Minitab. Everything is with steps, snapshots, and examples, which will be very easy to understand.

Preview 05:46
+ Detailed Illustration of "Correlation and Regression Concepts" with example
1 lecture 09:05

Hello Friends,

We can use scatter plots to understand the relationships between variables, but it is applied only for obvious relationships like Temperature and Viscosity. Sometimes, it is not possible to comment about relationship between variables only looking at the graph.

The “CORRELATION & REGRESSION” are very important mathematical concepts to define relationship between variables. This is the topic for video.

I have tried to explain these concepts with the help of practical examples which will be very easy to understand. I have also explained the procedure about how to create a “CORRELATION & REGRESSION ANALYSIS” in Microsoft Excel. Everything is with steps, snapshots and examples, which will be very easy to understand.

I have also covered statistics part like how to read and understand “SIGNIFICANCE F and P-values”

I am sure, you will liked it.

Preview 09:05
+ Regression Analysis: Types and Illustration of each type with practical example
4 lectures 36:08

Hello Friends,

            By considering all your valuable comments, I am advancing topic of “Nonlinear Regression” in this video, mainly comments from the video on “Correlation and Regression”. This video is mainly focused on Regression analysis, it’s types and Nonlinear Regression in very detailed along with practical example.

            Nonlinear Regression analysis is used to mathematically describe the nonlinear relationship between a response variable and one or more predictor variables. Specifically, use nonlinear regression instead of “ordinary least squares regression” when you cannot adequately model the relationship with linear parameters.

            I am going to explain this tool with practical example for easy understanding and better clarity. This video contains following topics:

1) What is Regression Analysis and their types?

2) Brief explanation all types of Regression Analysis methods

3) When to use Nonlinear Regression Analysis?

4) Data considerations for Nonlinear Regression

5) Nonlinear Regression Analysis with Practical Example in Microsoft Excel

6) Interpretation of results from Regression analysis including R-Square, Significance F and p-values, Coefficients, Residuals and Best Fit Model for Nonlinear Regression

            I am sure, you will like it.

Regression Analysis: Types and Nonlinear Regression Analysis
11:11

Hello Friends,

            By considering your valuable voting on community to select a topic that is important for you, we are going to continue the 2nd part of Nonlinear Regression in this video. In the 1st part of Nonlinear Regression, we had seen “What is nonlinear regression” and “It’s detailed illustration in Microsoft excel with practical example”.

            We are going to learn Nonlinear Regression Analysis in Minitab with the same practical example, we had seen in the last video. Nonlinear Regression analysis is used to mathematically describe the nonlinear relationship between a response variable and one or more predictor variables.

            I am going to explain this tool with practical example for easy understanding and better clarity. This video contains following topics:

1) Data considerations for Nonlinear Regression in Minitab

2) Nonlinear Regression Analysis with Practical Example in Minitab

3) Detailed Interpretation of results from Regression analysis in Session Window including Iterations of Convergence Criteria, Null hypothesis in Nonlinear Regression, Confidence Interval, Lack of fit test, S (Standard Deviation of Residuals) value and warning message

4) Detailed Interpretation of results from Regression analysis in Graph Window including Fitted Line plot, Residual plot, Histogram, Normal Probability Plot, Residuals versus the fitted values Plot, Residuals versus order Plot.

            I am sure, you will like it.

Nonlinear Regression Analysis: Illustration with Practical Example in Minitab
10:27

Hello Friends,

            We are continuing to learn the topic of Regression analysis by considering your valuable comments. So far, as a part of Regression Analysis, we had seen detailed study of Ordinary Least Square Regression and Nonlinear Regression.

            In this video, we are going to learn next type of Regression analysis i.e. Logistic Regression Analysis. There will be series of videos explaining Logistic Regression Analysis with its application, various types of it and detailed illustration of each type with practical example for easy understanding from this video onward.

            This video contains following topics:

1) What is Logistic Regression Analysis?

2) Types of Logistic Regression Analysis with Example

3) Link Function in Logistic Regression Analysis

4) Data Considerations for Logistic Regression Analysis

            I am sure, you will like it.

Logistic Regression Analysis: Introduction, Types and Data Considerations
07:36

Hello Friends,

            We had started learning of Logistic Regression analysis from last video along with its introduction and various types of it.

            In this video, we are going to learn 1st type of Logistic Regression analysis i.e. Binary Logistic Regression. The Binary Logistic Regression is used to perform logistic regression on a binary response variable.

            A binary variable only has two possible values, such as Pass or Fail.

            This video contains following topics:

1) What is Binary Logistic Regression Analysis?

2) Data considerations for Binary Logistic Regression

3) Detailed Illustration of Binary Logistic Regression Analysis with Practical Example

4) Detailed Procedure for Analysis in Minitab

5) Interpretation of Results in Session Window

6) Interpretation of Results in Graph Window

            I am sure, you will like it.

Binary Logistic Regression: Detailed Illustration with Practical Example
06:54
+ Quiz
0 lectures 00:00

Let's see your understanding related to course...

Quiz for Correlation and Regression
4 questions
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 02 sections.

Section-1: This will be explained-

  • Correlation

  • Correlation Analysis

  • Calculating Correlation Coefficient

  • Practical use of Correlation and Regression with a practical example

  • Regression

  • Significance F and p-values

  • Coefficients

  • Residual and

  • Conclusion

Section-2: This will be explained-

  • Types of Regression Analysis

  • Practical use of each Regression Analysis with Example

  • Use of Minitab to conduct Regression Analysis

  • Interpretation of Results

I am sure you will be liked it...

Who this course is for:
  • Students
  • Professionals