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Correlation measures the strength and direction of the linear relationship between two variables, providing a coefficient that ranges from -1 to 1. In contrast, regression goes further by modeling the relationship, allowing for predictions of one variable based on another. While correlation simply indicates whether a relationship exists, regression quantifies the relationship and can account for additional variables. Both are valuable statistical tools, but they serve different purposes in data analysis.
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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 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.
Why is the independent variable the only thing that changes?
It is not. If it were, there would be no regression or correlation.
What is the geometric basis for the math behind correlation and regression?
Z Test
Is the slope of a line positive when doing linear regression if the correlation coefficient is negative?
No, the slope of a line in linear regression cannot be positive if the correlation coefficient is negative. The correlation coefficient measures the strength and direction of a linear relationship between two variables; a negative value indicates that as one variable increases, the other decreases. Consequently, a negative correlation will result in a negative slope for the regression line.
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 correlation and regression?
correlation we can do to find the strength of the variables. but regression helps to fit the best line
Can a correlation problem also be a regression problem?
Yes.
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.
Use of correlation and regression in business?
"http://wiki.answers.com/Q/Use_of_correlation_and_regression_in_business"
What is the term for two things that predict each other?
correlation, or regression
What is the geometric basis for the math behind correlation and regression?
Z Test
Why is the independent variable the only thing that changes?
It is not. If it were, there would be no regression or correlation.
What is the process of directing and determining among variable?
Regression Analysis
Is the slope of a line positive when doing linear regression if the correlation coefficient is negative?
No, the slope of a line in linear regression cannot be positive if the correlation coefficient is negative. The correlation coefficient measures the strength and direction of a linear relationship between two variables; a negative value indicates that as one variable increases, the other decreases. Consequently, a negative correlation will result in a negative slope for the regression line.
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 negative correlation indicate?
the negative sign on correlation just means that the slope of the Least Squares Regression Line is negative.
