D E G H 0 P 5 T n D K LM N DA Ten The One Tour D IN TY SES 22 > GE 02 Now HE 13 G SU ME the icon 10 15 SUMMARY OUTPUT 29 18 ODE OTT 20 M R 7000 Samo 7361 03 19 45 G 24 ANIMA 24 GE B6 3600 LE 23 Rei To MIT SE F 9 VE SITE CE 56 MO 14 15 20 can Sand 51 05/17342 2 Age 15.12.2011 2 3 Wochenende With pow? 9 What does the main What do Ito SE set weather of the count Acu GO Average Sumo VES 918 Olonnaire English (Canada) le 2840 M L OM Salary 525 fo =df A B D E F G H 1 Question 3 2 3 The Univers.ty of Toronto is reviewing data on each of es faculty members 4 5 The variables are 5 test score when the first applied for ser position 44 54 7 Present go 50 8 22 Evaluation by students 521 05 9 Number of articles she has written g 42 10 415 103 11 12. The following computer output considers Salary and Age and Articles 13 14 15 SUMMARY OUTPUT 26 Regression Statistics 18 MR 034927076085 19R Square 0.72120079127 20 Adjusted R Square 0.70619380701 21 Standard Emor 73451147190 22 Observations 40 -3 4 ANOVA 5 SSS MS Sonhance 6 Regression 25105 2714708087506357354 47 870087404544708513E-11 7 Residual 37 1996.17697919253 9507102484 30 716144775 9 Comics 0 Standard Error Star Pal Lower 95 ON Linger or 930 1 Intercept 58 6461305492 8 3797836378359 349740340292 7795458E-11 246 7134010054372 5728000/1946 719-4610964 72.5728000/19 2 Woo 0 1820561931 0.544759644275-125/5446565 0 21640020003 0.475.X170932TTO 11125470709 -0.475.3670933 0 11125470709 3 Articles 1093718001020113216004379 00045211011 106450F 11 01:43210699111223116258120,0643210001032311625312 4 5 Which variables) is the independent variable? 6 7 Which variable is the dependent ble? 3 2 What does the multiple R tells us? L M N O P DATA Test Score Agol Sala Erwin Widers 53 41 50 504 32 621 12 64 100 6 59 42 571 5.76 582 40 542 6.40 54 33 61 02 12 311 63 6 10 541 AR 832 645 61 471 495 7:20 2 81 50 75 810 21 27 SC 65 0.40 625 404 630 62 683 41 570 3 51 63 25 820 655 21 057 103 84 4 090 940 29 54 30 58 7.00 4 365 651 60 11 4436 52 620 7 7200 704 6011 20 6543 36 024 64039 750 7.00 22 80 490 55 1 40 85 28 570 23 735 22 528 34 1841 5.81 2 71 30 830 TS 1 55 35 773 7.30 18 620 50 50 5.74 58 45 570 6.61 4 71 20 455 740 00 511 583 1 701 34 09 685 361 60 603 9 717 50 55 523 681 40 616 5.40 14 450 40 50 652 15 61.6 44 801 730 34 560 71.1 777 10 255 8 T 1 What does RSquare tellus 3 using the numbers provided what is the regression equation 5 Use to what to explain the effect of the x coefficient LISASI P M N 0 DATA Lored SEIS 41 1 SEN 21 67 1 B2 50 U 441 CHE 3 10 25 GI 41 20 310 31 6200 40 31 DE TY 5130 2 163 09 63 011 018 JOB . 11 B 1 Questions D G H The University of Toronto is reviewing data on each of its faculty members The variables are Teste wen he/she ftped her portion Presentage 8 Evaluation by students 9 Number of redeschi 32 1 10 0 43 11 415 100 12 The following computer output conuders Salary and Artides 13 14 15 SUMMARY OUTPUT 16 17 Regressionalistes 18 Multiple R 08422263901 19 R Square 0.7093452022 20 Adused R Square 0.7016064841 21 Standard Error 74011174538 22 Observations 40 23 24 ANOMA 25 ss Bencana 26 Regression 107090051107027393230916E-12 27 Residual 38 2001 56850349 54 776539566 28 Total 39 716144775 29 30 Constandard Pa Zower 93 LEO 31 bercept 51 4290066 1.7601742 23.864451837 1 DE 27 4030248503765833 48 30465632 555533305 32 Articles 100002154 154005223456301258322 052911120007240095162015102872400132010348 33 34 35 Which variables) is the independent variatie? 36 37. Which variable is the dependent variable? 38 39 What does the multiple R teisus? 40 41 What does RSquarelus? 42 43 Using the numbers provided what is the regression equation 44 45 Use to what to explain the effect of the coffent ES 440 SE 72 100 054 58 GA GE 23 RE 7.00 BE 603 22 24 22 TE BK 751 SY 884 58.4 13 BE 820 303 S70 2 BE 33 31 70.0 n 22 4 1 4 11 740 58 66 523 520 25 7 700 50 55 40 81 10 307 GC B01 71 2 16 30 LE Activate w Go to Settindi Average 44 Sum