Questions: Shown below is the output from a linear model predicting armspan (in cm) from height (in inches) and summary statistics. Assume that the association between armspan and height is linear. Use the output and summary statistics to complete parts a through d. LinReg y=a+bx a=27.336548588 b=2.085486727 Height, x: 63.59, 3.58 Armspan, y: 159.95, 7.70 a. Report the regression equation, using the words "Height" and "Armspan," not x and y. A. Predicted Armspan = 2.09 + 27.34 Height B. Predicted Height = 27.34 + 2.09 Armspan C. Predicted Armspan = 27.34 + 2.09 Height D. Predicted Height = 2.09 + 27.34 Armspan

Shown below is the output from a linear model predicting armspan (in cm) from height (in inches) and summary statistics. Assume that the association between armspan and height is linear. Use the output and summary statistics to complete parts a through d.
LinReg
    y=a+bx
    a=27.336548588
    b=2.085486727
Height, x: 63.59, 3.58
Armspan, y: 159.95, 7.70
a. Report the regression equation, using the words "Height" and "Armspan," not x and y.
A. Predicted Armspan = 2.09 + 27.34 Height
B. Predicted Height = 27.34 + 2.09 Armspan
C. Predicted Armspan = 27.34 + 2.09 Height
D. Predicted Height = 2.09 + 27.34 Armspan
Transcript text: Shown below is the output from a linear model predicting armspan (in cm ) from height (in inches) and summary statistics. Assume that the association between armspan and height is linear. Use the output and summary statistics to complete parts a through d. LinReg y=a+bx a=27.336548588 b=2.085486727 Height, $x$ & 63.59 & 3.58 Armspan, $y$ & 159.95 & 7.70 a. Report the regression equation, using the words "Height" and "Armspan," not $x$ and $y$. A. Predicted Armspan $=2.09+27.34$ Height B. Predicted Height $=27.34+2.09$ Armspan C. Predicted Armspan $=27.34+2.09$ Height D. Predicted Height $=2.09+27.34$ Armspan
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Solution

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Solution Steps

Step 1: Identify the regression equation

The regression equation is given in the form \( y = a + bx \), where:

  • \( y \) is the dependent variable (Armspan)
  • \( x \) is the independent variable (Height)
  • \( a \) is the y-intercept
  • \( b \) is the slope

From the given data:

  • \( a = 27.336548588 \)
  • \( b = 2.085486727 \)
Step 2: Substitute the variables into the equation

Substitute the given values into the regression equation: \[ \text{Armspan} = 27.34 + 2.09 \times \text{Height} \]

Step 3: Match the equation with the given options

Compare the derived equation with the provided options:

  • Option A: Predicted Armspan = 2.09 + 27.34 Height
  • Option B: Predicted Height = 27.34 + 2.09 Armspan
  • Option C: Predicted Armspan = 27.34 + 2.09 Height
  • Option D: Predicted Height = 2.09 + 27.34 Armspan

The correct match is: \[ \text{Option C: Predicted Armspan} = 27.34 + 2.09 \times \text{Height} \]

Final Answer

Option C: Predicted Armspan = 27.34 + 2.09 Height

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