7.35

(a)

Explanatory variable: height

Response variable: weight

The relationship is a positive strong correlation between height and weight

(b)

\[ \hat{weight} = -105.0113 + 1.0176 * height \]

slope= 1.0176

This indicates that each additional cm of height is associated with 1.0176 kg of weight.

intercept = -105.0113

This indicates that if the linear model is correct, then a height of 0 cm is associated with a weight of -105 kg which doesn’t make sense

(c)

H(o): The true slope coefficient of height is zero

H(A): The slope coefficient of height is greater than zero

Since the p-value is incredibly small we can reject the null hypthesis The data has significant evidence that height and weight are correlated

(d)

\[ R^{2} = 0.72^{2} = 0.52 \] This means that 52% of the variability in weight can be explained by the height variable yu