Given co-efficient of determination, r2 = 0.81.
co-efficient of correlation, r = square root of 0.81
= +0.9, if the data have move in the same direction.(Let x and y as variables then x and y have linear relationship and x increase or decrease and y also have increase or decrease)
= -0.9, if the data have move in the opposite direction.(Let x and y as variables then x and y have linear relationship and x decrease or increase and y is also increase or decrease)
coefficient of determination
It's not quite possible for the coefficient of determination to be negative at all, because of its definition as r2 (coefficient of correlation squared). The coefficient of determination is useful since tells us how accurate the regression line's predictions will be but it cannot tell us which direction the line is going since it will always be a positive quantity even if the correlation is negative. On the other hand, r (the coefficient of correlation) gives the strength and direction of the correlation but says nothing about the regression line equation. Both r and r2 are found similarly but they are typically used to tell us different things.
The coefficient of determination R2 is the square of the correlation coefficient. It is used generally to determine the goodness of fit of a model. See: http://en.wikipedia.org/wiki/Coefficient_of_determination for more details.
= CORREL(x values,y values) ***clarification**** CORREL gives you the correlation coefficient (r), which is different than the coefficient of determination (R2) outside of simple linear regression situations.
No, it cannot be a correlation coefficient.
Yes it can be a correlation coefficient.
A correlation coefficient is a numerical measure of the
No. The strongest correlation coefficient is +1 (positive correlation) and -1 (negative correlation).
A coefficient of zero means there is no correlation between two variables. A coefficient of -1 indicates strong negative correlation, while +1 suggests strong positive correlation.
the correlation coefficient range is -1 to +1
A serious error. The maximum magnitude for a correlation coefficient is 1.The Correlation coefficient is lies between -1 to 1 if it is 0 mean there is no correlation between them. Here they are given less than -1 value so it is not a value of correlation coefficient.
partial correlation is the relation between two variable after controlling for other variables and multiple correlation is correlation between dependent and group of independent variables.
The correlation coefficient must lie between -1 and +1 and so a correlation coefficient of 35 is a strong indication of a calculation error. If you meant 0.35, then it is a weak correlation.
Evidence that there is no correlation.
A coefficient of correlation of 0.70 infers that there is an overall correlation between the trends being compared. The correlation is not perfect, but enough to be acknowledged and researched further.
No. Correlation coefficient is measured from +1 to -1. In addition, if the two sets of exam are exactly same, their correlation coefficient is +1.
correlation is a difference in statistics
A correlation coefficient of zero means that two things are not correlated to each other.
34.32245Correlation coefficient is less than -1 and greater than 1.Note: The Correlation coefficient is lies between -1 to 1 if it is 0 mean there is no correlation between them.
No, it depends upon the size of the coefficient of correlation: the closer to Â±1 the stronger the correlation.When the correlation coefficient is positive, one variable increases as the other increases; when negative one increases as the other decreases.
Why the value of correlation coefficient is always between -1 and 1?
Assume that you are correlating two variables x and y. If there is an increasing relationship between x and y, (that is , the graph of y=a+bx, slopes upward), the correlation coefficient is positive. Similarly, if there is a decreasing relationship, the correlation coefficient is negative. The correlation coefficient can assume values only between -1 and 1.
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. .