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.
"Strong" is very much a subjective term. Not only that, but it depends on expectations. In economics I would consider 70% to be a strong correlation, but for physics I would want more than 95% before I called the correlation strong!
No.
a strong negative correlation* * * * *No it is not. It is a very weak positive correlation.
If the form is nonlinear (like if the data is in the shape of a parabola) then there could be a strong association and weak correlation.
No, The correlation can not be over 1. An example of a strong correlation would be .99
The correlation can be anything between +1 (strong positive correlation), passing through zero (no correlation), to -1 (strong negative correlation).
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.
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.
"Strong" is very much a subjective term. Not only that, but it depends on expectations. In economics I would consider 70% to be a strong correlation, but for physics I would want more than 95% before I called the correlation strong!
No.
A perfect positive correlation would be exactly 1; 1.00 means "0.995 or higher", which is quite strong indeed.
a strong negative correlation* * * * *No it is not. It is a very weak positive correlation.
No, it indicates an extremely strong positive correlation.
If the form is nonlinear (like if the data is in the shape of a parabola) then there could be a strong association and weak correlation.
The graph follows a very strong downward trend. Would have helped if you specified which correlation coefficient; there are different types.
It tells you how strong and what type of correlations two random variables or data values have. The coefficient is between -1 and 1. The value of 0 means no correlation, while -1 is a strong negative correlation and 1 is a strong positive correlation. Often a scatter plot is used to visualize this.