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Homework 2 ::: 10 Points OPRE 6301If you've any questions, please contac the TAInstructions:This is a required HW. 2. Enter your name below and on every sheet.4. Click on the tabs below to work on the 3 sets of problems.5. Do all your work in the proper cells only. Copy-and-paste deal is not al6. While working on the HW, save your file periodically to avoid losing you7. Don't wait till the last minute. You may get into technical / internet relateThis HW is to be worked out by each student independently. Collabowill result in a score of 0 and your case will be reported to thFailure to follow submission guidelines will cost 3 points.Name:ABHIJIT PATILScores:(Do not write below this line.)ProblemPointsEarnedSet 17Set 26Set 34Set 43Total2001. Save and rename this file as Lastname-Firstname-HW2 (Sethi-Avant3. When you are done, submit it through eLearning only.
llowed. ur work accidentally.ed problems. No EXCUSE!oration of any formhe university authority. ti-HW2, for example).
Scatter PlotyXPredictedResidualResidual-squared202824.08145106 4.08145106116.6582427627333832.37713895 -0.622861050.3879558927282824.08145106 -3.9185489415.355025788152219.104038334.1040383316.8431306134191815.78576318 -3.2142368210.3313183614273126.57015743 -0.429842570.1847646381Correlation:0.858559359Sum of residual squared:59.7604380561SUMMARY OUTPUTRegression StatisticsName:ABHIJIT PATILA dataset has been given which has 2 variables - X and Y. Draw a scatter diagram and find the correlation coefficient in Cell B29. Change the numbers in X column (any which way you want) to get the correlation coefficient to be between .83 and .86. This will require some trial and error. You'll see the changes in the scatter plot and the correlation coefficient as you change X values. Now use Data Analysis to run the regression program. Check the boxes for the Residual and Residual Plot boxes. Send the output to Cell A46. Use the regression intercept and slope (that is, Regression equation) to predict the value of Y for each X in the table below (Column = Predicted; use the cell references directly as opposed to typing in the values). Compare this predicted value of Y to the actual value of Y. The difference is called Residual (error). Compare these residuals to the Residuals given by Excel's Regression function. They should match exactly. Now square the residuals and add them up in Cell E29. This sum should match to the SS (Sum Squared) value given by Excel.