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

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Q: What is the difference between correlation and regression?
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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 is the difference between Multicollinearity and Autocorrelation?

The difference between multicollinearity and auto correlation is that multicollinearity is a linear relationship between 2 or more explanatory variables in a multiple regression while while auto-correlation is a type of correlation between values of a process at different points in time, as a function of the two times or of the time difference.


What is a line that shows the correlation between two data sets called?

There is no line that shows the correlation between two data sets. The correlation is a variable that ranges between -1 and +1.You may be thinking about regression which, although related, is not the same thing.There is no line that shows the correlation between two data sets. The correlation is a variable that ranges between -1 and +1.You may be thinking about regression which, although related, is not the same thing.There is no line that shows the correlation between two data sets. The correlation is a variable that ranges between -1 and +1.You may be thinking about regression which, although related, is not the same thing.There is no line that shows the correlation between two data sets. The correlation is a variable that ranges between -1 and +1.You may be thinking about regression which, although related, is not the same thing.


What is the relationship between correlation coefficient and linear regreassion?

A correlation coefficient is a value between -1 and 1 that shows how close of a good fit the regression line is. For example a regular line has a correlation coefficient of 1. A regression is a best fit and therefore has a correlation coefficient close to one. the closer to one the more accurate the line is to a non regression line.


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

A linear regression


What is the difference between ratio estimation and regression estimation?

diferece between ratio and regression


What is the difference between correlation analysis and regression analysis?

In linear correlation analysis, we identify the strength and direction of a linear relation between two random variables. Correlation does not imply causation. Regression analysis takes the analysis one step further, to fit an equation to the data. One or more variables are considered independent variables (x1, x2, ... xn). responsible for the dependent or "response" variable or y variable.


What is the difference between the population and sample regression functions Is this a distinction without difference?

What is the difference between the population and sample regression functions? Is this a distinction without difference?


What are the properties of correlation?

The correlation coefficient is symmetrical with respect to X and Y i.e.The correlation coefficient is the geometric mean of the two regression coefficients. or .The correlation coefficient lies between -1 and 1. i.e. .


Difference between Multicollinearity and Autocorrelation?

Multicolinearity shows the relationship of two or more variables in a multi-regression model. Auto-correlation shows the corellation between values of a process at different point in times.