Can someone show me an example for solving thie. Thanks! Refer to the Problem 2
ID: 3045992 • Letter: C
Question
Can someone show me an example for solving thie. Thanks!
Refer to the Problem 2 tab in the Excel file. Determine what height the model would predict for you. In the space below, explain how you predicted your height. Next, compare your actual height to the height predicted for you by the model. Is your error term (residual) positive or negative, or did the model work perfectly for you? If you examined all the error terms for a group of 100 people who all wore your shoe size, what would you expect to see? Type your answer into the box below--I will grade these separately.
AutoSave Stats Excel nick Jacka Insert Draw Page Layout Formulas Data Review View Help Tell me what you want to do Share Cut Copy Format Painter Calibri 11A A Ee wrap Text General B , w-·2.A ,- . Merge & Center s-% , ,g Conditional Fonmat as Cell Insert Delete Fo rmatClear. Sort & Find & Filter Select · FormattingTable Styles' Clipboard Alignment Cells Editing A1 | Problem 2 In past years when I taught BUS 305 in the classroom, we would often gather data from students on their height in inches and their dress shoe size. A subset of that data was used to create the regression model here, where shoe size serves as the independent x) variable and height as the dependent (y) variable SUMMARY OUTPUT Rearession Stotistics Multiple R R Square Adjusted R Square Standard Error Observations 0.8942 0.7996 0.7961 1.9020 60 10 Use the regression results to answer the questions in Blackboard. 12 ANOVA MS 16 Regression Residual Total 0.0000 837.2513 837.2513 231,4259 209.8320 3.6178 58 59 1047.0833 Coefficients Standard Error tStatP-value Intercept Shoe Size 49.4108 1.9014 1.2840 38.4821 0.0000 0.1250 15.2127 0.0000 Instructions Problem 1 Problem 2 E- + 100% Type here to search 9:31 PM 2/17/2018Explanation / Answer
Sol:
shoe size-y
height -x
regression model form output is
height=49.4108+1.9014(shoe size)
slope of regression line=1.9014
y intercept=49.4108
R sq=0.7996
79.96% variation is height is explained by shoe size
Good model.
From Anova Table
F=231.4259
p=0.0000
p<0.05
Model is significant.
Provide sample data to find the actual and predicted values and then Residuals.
If random pattern is observed in Residual plot.Model is good.