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Heights (cm) and weights (kg) are measured for 100 randomly selected adult males, with heights ranging from 130 to 190 cm and weights from 39 to 150 kg. Let the predictor variable [tex]$x$[/tex] be the height.

The 100 paired measurements yield the following:

- [tex]$\bar{x} = 167.99 \text{ cm}$[/tex]
- [tex]$\bar{y} = 81.57 \text{ kg}$[/tex]
- [tex]$r = 0.382$[/tex]
- [tex]$\hat{y} = -109 + 1.07x$[/tex]

Find the best predicted value of [tex]$\hat{y}$[/tex] (weight) given an adult male who is 182 cm tall.

The best predicted value of [tex]$\hat{y}$[/tex] for an adult male who is 182 cm tall is [tex]\square[/tex] kg. (Round to two decimal places as needed.)

Answer :

To find the best predicted value of [tex]\(\hat{y}\)[/tex] (weight) for an adult male who is 182 cm tall, we use the provided linear regression equation:

[tex]\[
\hat{y} = -109 + 1.07x
\][/tex]

Here, [tex]\(\hat{y}\)[/tex] represents the predicted weight, and [tex]\(x\)[/tex] represents the height in centimeters.

Step-by-step Solution:

1. Identify the given height: The problem states that we need to predict the weight for an adult male who is 182 cm tall. Thus, [tex]\(x = 182\)[/tex].

2. Substitute the height into the regression equation: Replace [tex]\(x\)[/tex] in the equation with 182:

[tex]\[
\hat{y} = -109 + 1.07 \times 182
\][/tex]

3. Calculate the predicted weight: Perform the multiplication and addition:

- First, calculate [tex]\(1.07 \times 182\)[/tex]:
[tex]\[
1.07 \times 182 = 194.74
\][/tex]

- Then add [tex]\(-109\)[/tex] to this result:
[tex]\[
\hat{y} = -109 + 194.74 = 85.74
\][/tex]

Thus, the best predicted value of [tex]\(\hat{y}\)[/tex] for an adult male who is 182 cm tall is [tex]\(85.74\)[/tex] kg, rounded to two decimal places.

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