The 16% variability in weight can be explained by the relationship with height.
What is correlation?
In statistics, there are three different forms of correlation: positive, negative, and no correlation.
The link between two variables is said to be positive correlated when both variables move in the same direction. When one variable decline (or grows) while the other variable lowers (or increases), there is a positive perfect correlation, denoted by the number +1.
When two variables are correlated negatively, both of the variables are moving in the opposing direction. When one variable rises (or falls) while the other rises (or falls), there is a negative perfect correlation, which is symbolised by the number -1.
No correlation, which is represented by 0, means that there is no connection or reliance between the two variables.
On the basis of provided information, the correlation between the height and weight for adults is,
r = +0.4
So, the coefficient of determination is calculated as,
[tex]r^{2} = (0.40)^{2}[/tex] = 0.16 = 16%
Based on the provided information, the required answer is 16%.
To learn more about the correlation
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