CORRELATION & REGRESSION ANALYSIS (QT for MBA Students)
Introduction to Correlation and Regression Analysis
In this section we will first discuss correlation analysis, which is used to quantify the association between two continuous variables (e.g., between an independent and a dependent variable or between two independent variables). Regression analysis is a related technique to assess the relationship between an outcome variable and one or more risk factors or confounding variables. The outcome variable is also called the response or dependent variable and the risk factors and confounders are called the predictors, or explanatory or independent variables. In regression analysis, the dependent variable is denoted “y” and the independent variables are denoted by “x“.
Correlation Analysis
In correlation analysis, we estimate a sample correlation coefficient, more specifically the Pearson Product Moment correlation coefficient. The sample correlation coefficient, denoted r,
ranges between 1 and +1 and quantifies the direction and strength of the linear association between the two variables. The correlation between two variables can be positive (i.e., higher levels of one variable are associated with higher levels of the other) or negative (i.e., higher levels of one variable are associated with lower levels of the other).
The sign of the correlation coefficient indicates the direction of the association. The magnitude of the correlation coefficient indicates the strength of the association.
For example, a correlation of r = 0.9 suggests a strong, positive association between two variables, whereas a correlation of r = 0.2 suggest a weak, negative association. A correlation close to zero suggests no linear association between two continuous variables
Course Features
 Lectures 11
 Quizzes 0
 Duration 50 hours
 Skill level All levels
 Language English
 Students 5
 Certificate No
 Assessments Yes

INTRODUCTION TO CORRELATION
This section describes what is correlation and various types of correlation

METHODS OF MEASURING CORRELATIONKarl Pearsons coefficient of correlation
This section describes various methods to measure correlation

Karl  Pearsons coefficient of correlation
This section explains the shortcut method of computing Karl Pearsons coefficient of correlation

RANK CORRELATION METHOD
This section explains the method of applying the method of Rank Correlation

RANK CORRELATION METHOD when ranks are not given
This section explains how to put ranks and calculate Rank correlation coefficient

RANK CORRELATION METHOD  REPEATED RANKS

REGRESSION ANALYSISBASIC CONCEPTS
This section explains Regression Analysis

REGRESSION ANALYSIS
This section explains how to fit two Regression lines

REGRESSION ANALYSIS shortcut method

REGRESSION ANALYSIS  RELATION BETWEEN REGRESSION COEFFICIENTS AND CORRELATION COEFFICIENTS
This section explains how to compute correlation coefficient from regression coefficients

MEAN VALUES AND STANDARD DEVIATIONS FROM REGRESSION EQUATIONS
This section describes how to find out mean values from Regression equations