Regression Statistics Multiple R 01347 R Square 00181 Adjust

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

Solution

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