Homework Heights \( (\mathrm{cm}) \) and weights \( (\mathrm{kg}) \) are measured for 100 randomly selected adult males, and range from heights of 138 to 192 cm and weights of 39 to 150 kg . Let the predictor variable \( x \) be the first variable given. The 100 paired measurements yield \( \bar{x}=167.53 \mathrm{~cm}, \bar{y}=81.41 \mathrm{~kg}, \mathrm{r}=0.305, \mathrm{P} \)-value \( =0.002 \), and \( \hat{y}=-101+1.02 \mathrm{x} \). Find the best predicted value of \( \hat{y} \) (weight) given an adult male who is 167 cm tall. Use a 0.01 significance level. - Click the icon to view the critical values of the Pearson correlation coefficient r . The best predicted value of \( \hat{y} \) for an adult male who is 167 cm tall is \( \square \mathrm{kg} \).
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To find the best predicted value of \( \hat{y} \) (weight) for an adult male who is 167 cm tall, you can substitute \( x = 167 \) cm into the regression equation \( \hat{y} = -101 + 1.02x \). So, \[ \hat{y} = -101 + 1.02(167) = -101 + 170.34 = 69.34 \text{ kg}. \] Thus, the best predicted value of \( \hat{y} \) for an adult male who is 167 cm tall is approximately \( 69.34 \) kg. Given the \( P \)-value of \( 0.002 \), which is less than the significance level of \( 0.01 \), we can conclude that the correlation between height and weight is statistically significant.