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Q: Does The strength of the correlation between two variables A regression equation is a mathematical equation that defines the relationship between two variables?
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What is regression coefficient and correlation coefficient?

The strength of the linear relationship between the two variables in the regression equation is the correlation coefficient, r, and is always a value between -1 and 1, inclusive. The regression coefficient is the slope of the line of the regression equation.


What are the advantages of regression over correlation?

Correlation is a measure of association between two variables and the variables are not designated as dependent or independent. Simple regression is used to examine the relationship between one dependent and one independent variable. It goes beyond correlation by adding prediction capabilities.


Distinguish between correlation and regression?

Correlation is a measure of the degree of agreement in the changes (variances) in two or more variables. In the case of two variables, if one of them increases by the same amount for a unit increase in the other, then the correlation coefficient is +1. If one of them decreases by the same amount for a unit increase in the other, then the correlation coefficient is -1. Lesser agreement results in an intermediate value. Regression involves estimating or quantifying this relationship. It is very important to remember that correlation and regression measure only the linear relationship between variables. A symmetrical relationshup, for example, y = x2 between values of x with equal magnitudes (-a < x < a), has a correlation coefficient of 0, and the regression line will be a horizontal line. Also, a relationship found using correlation or regression need not be causal.


Is the regression equation a mathematical equation that defines the relationship between two variables?

No. It is an estimated equation that defines the best linear relationship between two variables (or their transforms). If the two variables, x and y were the coordinates of a circle, for example, any method for calculating the regression equation would fail hopelessly.


What do researchers use to represent graphically the correlation between two variables?

A linear regression

Related questions

What is regression coefficient and correlation coefficient?

The strength of the linear relationship between the two variables in the regression equation is the correlation coefficient, r, and is always a value between -1 and 1, inclusive. The regression coefficient is the slope of the line of the regression equation.


What are the advantages of regression over correlation?

Correlation is a measure of association between two variables and the variables are not designated as dependent or independent. Simple regression is used to examine the relationship between one dependent and one independent variable. It goes beyond correlation by adding prediction capabilities.


Distinguish between correlation and regression?

Correlation is a measure of the degree of agreement in the changes (variances) in two or more variables. In the case of two variables, if one of them increases by the same amount for a unit increase in the other, then the correlation coefficient is +1. If one of them decreases by the same amount for a unit increase in the other, then the correlation coefficient is -1. Lesser agreement results in an intermediate value. Regression involves estimating or quantifying this relationship. It is very important to remember that correlation and regression measure only the linear relationship between variables. A symmetrical relationshup, for example, y = x2 between values of x with equal magnitudes (-a < x < a), has a correlation coefficient of 0, and the regression line will be a horizontal line. Also, a relationship found using correlation or regression need not be causal.


What is the difference between correlation and regression?

correlation we can do to find the strength of the variables. but regression helps to fit the best line


Is the regression equation a mathematical equation that defines the relationship between two variables?

No. It is an estimated equation that defines the best linear relationship between two variables (or their transforms). If the two variables, x and y were the coordinates of a circle, for example, any method for calculating the regression equation would fail hopelessly.


When a pair of variables have a positive correlation will the slope in the regression equation always be positive?

Yes


What do researchers use to represent graphically the correlation between two variables?

A linear regression


What is Full Regression?

Regression :The average Linear or Non linear relationship between Variables.


What is the importance of correlation and regression analysis in business decision making?

Correlation and regression analysis can help business to investigate the determinants of key variables such as their sales. Variations in a companies sales are likely to be related to variation in product prices,consumers,incomes,tastes and preference's multiple regression analysis can be used to investigate the nature of this relationship and correlation analysis can be used to test the goodness of fit. Regression can also be used to estimate the trend in a time series to make forecast


If coefficient of correlation r between two variables is zero does it mean that there is no relationship between the variables Justify your answer?

"If coefficient of correlation, "r" between two variables is zero, does it mean that there is no relationship between the variables? Justify your answer".


What is positive Correlation?

Positive correlation is a relationship between two variables in which both variables move in tandem that is in the same direction.


What is a zero correlation?

a zero correlation means that there is no relationship between the two or more variables.