Question

Question 13 2.5 pts For Questions 13 - 22, consider the following scenario: An analyst for an e-commerce website would like to use a regression model to predict the total amount that customers spend per order. The analyst theorizes that income may help explain order total. An a = 0.05 significance level will be used for this analysis. The analyst randomly samples customers. Total Order Amount was measured in dollars, Income in thousands, The data was used to estimate a regression model. The regression output is given below. SUMMARY OUTPUT Regression Statistics Multiple R 0.88012 R Square 0.77461 Adjusted R Square 0.77190 Standard Error 56.6927 Observations 253 ANOVA Significance df E 285.2516 0 .000 Regression Residual Total SS MS 2750450.3598 916816.787 800301.86653 214.0637 3550752.226 251 252 t Intercept Income Coefficients 70.2382 5.4585 Standard Error 15.8338 0.2485 Stat 4.4360 21.9696 P-valueLower 95% 0.000014 3 9.053 0.000 4 .9692 Upper 95% 1 01.4234 5.9479

Answer 1

Solution-19:

since t=21.9696

p=0.000

p<0.05

Reject Ho

There is a linear relationship between x and y

ANSWER;

YES

Solution-20:

sum of squared residuals=SSE=800301.8665

OPTION A

Solution-21:

regresssion model is

$y=\beta 0+\beta 1x+e$

OPTION B

Solution-22:

y^=intercept+slope*x

=70.2382+5.4585*x1

OPTION A