Predictive Analytics Instructions: Put your name without fail on each page. Do t
ID: 3048067 • Letter: P
Question
Predictive Analytics Instructions: Put your name without fail on each page. Do the exam yourself, and sign a statement stating that you did not receive help from other persons besides the instructor. You may use a use the end of the excam for more space. Show your work. And, Remember, the Fore will be with you. Always Data Y hat 23 16 25 28 51 14 SUMMARY OUTPUT A Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.97688814 0.939080583 3.277208147 ANOVA Regression Residual Total 1 672.9797 3 32.22028 4 Standard Error Coefficients t Stat P-value 2.531468531 3.604616 0.702285 0.533087 3.43006993 0.433317 7.915839 0.004203 InterceptExplanation / Answer
1) X is significant to Y. The coefficient of P-value is less than 0.05 significant level. We can conclude that the predictor value is significant to an output variable.
2) To interpret slope, for every additional unit of X variable output variables increases by 3.433317 units.
3) Total sum of squares: SST= SSRegression+SSresidual= 672.9797+ 32.22028 = 705.2
4) Mean Square regression: MSR= SSRegression/DFregression = 672.9797/ 1 = 672.9797
Mean sqaure residual: MSE= SSresidual/DFResidual= 32.22028/3 = 10.74009
5) F- statistic = MSR / MSE = 672.9797/ 10.74009 = 62.66051
F critical: 3.5.
The test statistic is significant to f critical. and rejects null hypothesis. There is enough evidence to conclude that there is a significant difference between variables.
6) Y'= 2.531468531+ 3.433317*X
7) R-sqaure: SSregression/SSresidual = 672.9797/ 705.2 =0.95341
8) It is a good model. The calculated estimated percentage variance is 95.341% and explanatory variable is significant to an output variable.
Obs X Y Yhat 1 5 23 19.69805 2 5 16 19.69805 3 6 25 23.13137 4 8 28 29.998 5 14 51 50.59791