The stronger correlation will be the one whose absolute value is closest to one. For example, r = -.78 is stronger than r=.65, because:
|r| = |-.78| = .78 > |r| = |.65| = .65
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The further the correlation coefficient is from 0 (ie the closer to ±1) the stronger the correlation.Therefore -0.75 is a stronger correlation than 0.25The strength of the correlation is dependant on the absolute value of the correlation coefficient; the sign of the correlation coefficient gives the "relative" slope of correlation line:+ve (0 to +1) means that as one variable increases the other also increases;-ve (0 to -1) means that as one variable increases the other decreases.
Something is wrong. Correlations cannot be less than -1 or greater than 1.
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.
You can describe if there's any obvious correlation (like a positive or negative correlation), apparent outliers, and the corrlation coefficient, which is the "r" on your calculator when you do a regression model. The closer "r" is to either -1 or 1, the stronger that correlation is.
Any value between 0.40 and 1 or any value between -1 and -0.40.