Regression Statistics Multiple R 0.1347 R Square 0.0181 Adjusted R Square -0.057

Question

Regression Statistics

Multiple R

0.1347

R Square

0.0181

Adjusted R Square

-0.0574

Standard Error

3.384

Observations

15

ANOVA

df

SS

MS

F

Significance F

Regression

  1

    2.750

  2.75

0.2402

0.6322

Residual

13

148.850

11.45

Total

14

151.600

Coefficients

Standard Error

t Stat

p-value

Intercept

8.6  

2.2197

3.8744

0.0019

X

0.25

0.5101

0.4901

0.6322

none of the stated answers is correct

is 47.56

is 12.35

is 129.25

is 39.22

Shown below is a portion of an Excel output for regression analysis relating Y (dependent variable) and X (independent variable). If the variable X has the value 15 the predicted value of Y

Regression Statistics

Multiple R

0.1347

R Square

0.0181

Adjusted R Square

-0.0574

Standard Error

3.384

Observations

15

ANOVA

df

SS

MS

F

Significance F

Regression

  1

    2.750

  2.75

0.2402

0.6322

Residual

13

148.850

11.45

Total

14

151.600

Coefficients

Standard Error

t Stat

p-value

Intercept

8.6  

2.2197

3.8744

0.0019

X

0.25

0.5101

0.4901

0.6322

Answers:

none of the stated answers is correct

is 47.56

is 12.35

is 129.25

is 39.22

Explanation / Answer

The regression line is

y = 8.6+0.25*x

So the variable X has the value 15,

y= 8.6+0.25*15 =12.35

Answer: is 12.35

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