A positive correlation coefficient means that as the value of one variable increases, the value of the other variable increases; as one decreases the other decreases. A negative correlation coefficient indicates that as one variable increases, the other decreases, and vice-versa.
This means that the correlation is negative but still significant.
That as one variable increases so does the other
correlation measure the strength of association between to variables.but some times both variables are not in same units.so we cannot measure it with the help of correlation. in this case we use its coefficent which mean unit free. that,s why we use it.
It means that the two variables are likely dependent. The higher the number of the positive correlation the stronger the connection.
The graph follows a very strong downward trend. Would have helped if you specified which correlation coefficient; there are different types.
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. .
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. .
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.
A positive correlation coefficient means that as the value of one variable increases, the value of the other variable increases; as one decreases the other decreases. A negative correlation coefficient indicates that as one variable increases, the other decreases, and vice-versa.
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.
Of course it is! If the mean of a set of data is negative, then the coefficient of variation will be negative.
"If coefficient of correlation, "r" between two variables is zero, does it mean that there is no relationship between the variables? Justify your answer".
The correlation coefficient is a measure of linear association between two (or more) variables. It does not measure non-linear relationships nor does it say anything about causality.
Of course it is! If the mean of a set of data is negative, then the coefficient of variation will be negative.
This means that the correlation is negative but still significant.
Pearson's Product Moment Correlation Coefficient indicates how strong the relationship between variables is. A PMCC of zero or very close would mean a very weak correlation. A PMCC of around 1 means a strong correlation.