Size of variables
Yes, but the relationship need not be causal.
0
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.
impossible
The graph follows a very strong downward trend. Would have helped if you specified which correlation coefficient; there are different types.
Yes, but the relationship need not be causal.
Yes it can be a correlation coefficient.
No, it cannot be a correlation coefficient.
No, it depends upon the size of the coefficient of correlation: the closer to ±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.
A correlation coefficient quantifies the strength and direction of the relationship between two variables. Ranging from -1 to 1, a value of 1 indicates a perfect positive correlation, -1 indicates a perfect negative correlation, and 0 signifies no correlation. Higher absolute values indicate stronger relationships, while lower values suggest weaker or no relationships. It's important to note that correlation does not imply causation.
No. The strongest correlation coefficient is +1 (positive correlation) and -1 (negative 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. .
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.
the correlation coefficient range is -1 to +1
Evidence that there is no 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 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. .