A researcher would like to predict the dependent variable Y from the two independent variables X1...

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Statistics

A researcher would like to predict the dependent variable Y fromthe two independent variables X1 and X2 for a sample of N=12subjects. Use multiple linear regression to calculate thecoefficient of multiple determination and test statistics to assessthe significance of the regression model and partial slopes. Use asignificance level α=0.05.

  X1         X2         Y

34.426.459.4
53.738.390.4
72.843.271.3
25.421.264.5
75.946.571.1
60.427.972.6
2856.429.9
40.143.653.7
27.264.561.5
48.26043.8
78.653.653.5
6943.985.5

R2=
F=
P-value for overall model =

t1=
for b1, P-value =
t2=
for b2, P-value =

What is your conclusion for the overall regression model (alsocalled the omnibus test)?

  • The overall regression model is statistically significant atα=0.05
  • The overall regression model is not statistically significantat α=0.05


Which of the regression coefficients are statistically differentfrom zero?

  • neither regression coefficient is statisticallysignificant
  • the slope for the first variable b1 is the only statisticallysignificant coefficient
  • the slope for the second variable b2 is the only statisticallysignificant coefficient
  • both regression coefficients are statistically significant

Answer & Explanation Solved by verified expert
4.0 Ratings (635 Votes)

using excel data analysis tool for regression,steps are:

write data>menu>data>data analysis>regression>enter required labels>ok> and following o/p is obtained

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.645566
R Square 0.416756
Adjusted R Square 0.287146
Standard Error 14.26945
Observations 12
ANOVA
df SS MS F Significance F
Regression 2 1309.446 654.7232 3.215463 0.088375
Residual 9 1832.554 203.6171
Total 11 3142
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 67.90951 17.56506 3.866171 0.003811 28.17459 107.6444 28.17459 107.6444
X1 0.402109 0.214897 1.871172 0.094123 -0.08402 0.888239 -0.08402 0.888239
X2 -0.57943 0.315883 -1.83431 0.099811 -1.294 0.13515 -1.294 0.13515

R2=0.4168
F=3.2155
P-value for overall model =0.0884

t1=1.8712
for b1, P-value =0.0941
t2= -1.8343
for b2, P-value =0.0998

  • The overall regression model is not statistically significant at α=0.05

-------------------------

neither regression coefficient is statistically significant


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