HW2-6301-S16 - Homework 2 20 Points OPRE 6301 If you've any questions please contac the TA Instructions This is a required HW 1 Save and rename this

HW2-6301-S16 - Homework 2 20 Points OPRE 6301 If you've any...

This preview shows page 1 - 9 out of 45 pages.

Homework 2 ::: 20 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 allowed. 6. While working on the HW, save your file periodically to avoid losing your work a7. Don't wait till the last minute. You may get into technical / internet related probThis HW is to be worked out by each student independently. Collaboration owill result in a score of 0 and your case will be reported to the unFailure to follow submission guidelines will cost 3 points.Name:fang yi yangScores:(Do not write below this line.)ProblemPointsEarnedSet 18Set 27Set 35Set 45Total2501. Save and rename this file as Lastname-Firstname-HW2 (Sethi-Avanti-HW23. When you are done, submit it through eLearning only.
accidentally.blems. No EXCUSE!of any formniversity authority. 2, for example).
summary outputregression statisticsmultiple r0.943565236R square0.8903153546adjusted r square0.8628941933stadard eeror2.4967466854observations6ANOVAdfSSMSregression1202.39835729202.3983572895residual4 24.93497604386.233744011total5 227.333333333coefficientsstd errort statsintercept4.06502395623.5878727291.1329900092X var 10.91170431210.16000184825.6980861314residual outputobservationpredicted quantity residualsstandarized residuals122.2991101985-2.2991101985-1.0295330963229.59274469543.40725530461.5257564018329.5927446954-1.5927446954-0.7132252204413.18206707731.81793292270.8140636808520.4757015743-1.4757015743-0.6608137409626.85763175910.14236824090.063751975
Fsignificant f32.46818556140.0046874548p-valuelower 95%upper 95%lower 95%upper 95%0.320525684-5.8965077203 14.0265556327 -5.8965077203 14.02655563270.00468745480.46746796391.35594066030.46746796391.3559406603probability outputpercentageY8.333333333315251941.66666666672058.333333333327752891.666666666733
510152025-3-2-101234residual plotX variance 1residual010203040506070809005101520253035樣樣樣樣樣Y
30100
Name:___fang yi yang______yXPredictedResidualResidual-squared0.9117043121A dataset has been given which has 2 variables - X and Y. Draw a scatter diagram andcorrelation coefficient in Cell B29. Change the numbers in X column (any which way yget the correlation coefficient to be between .83 and .86. This will require some trial aYou'll see the changes in the scatter plot and the correlation coefficient as you changeNow use Data Analysis to run the regression pCheck the boxes for the Residual and Residual Plot boxes. Send the output to Cell A4regression intercept and slope (that is, Regression equation) to predict the value of Y fthe table below (Column = Predicted; use the cell references directly as opposed to tyvalues). Compare this predicted value of Y to the actual value of Y. The difference is cResidual (error). Compare these residuals to the Residuals given by Excel's RegressionThey should match exactly. Now square the residuals and add them up in Cell E29. should match to the SS (Sum Squared) value given by Excel. 202022.299-2.2995.286332829.5933.40711.609282829.593-1.5932.537151013.1821.8183.305191719.564-0.5640.318271719.5647.43655.294Correlation:0.845728337Sum of residual squared:78.3494.0650239562Th
Scatter Plotd find the you want) to and error.

  • Left Quote Icon

    Student Picture

  • Left Quote Icon

    Student Picture

  • Left Quote Icon

    Student Picture