chapter 1

More documents

Recommendations

Info

Chapter 11: Multifactor Analysis of Variance17.a.Source Df SS MS f F .05Sand 2 705 352.5 3.76 4.26Fiber 2 1,278 639.0 6.82* 4.26Sand&Fiber 4 279 69.75 0.74 3.63Error 9 843 93.67Total 17 3,105There appears to be an effect due to carbon fiber addition.b.Source Df SS MS f F .05Sand 2 106.78 53.39 6.54* 4.26Fiber 2 87.11 43.56 5.33* 4.26Sand&Fiber 4 8.89 2.22 .27 3.63Error 9 73.50 8.17Total 17 276.28There appears to be an effect due to both sand and carbon fiber addition to castinghardness.c.Sand% 0 15 30 0 15 30 0 15 30Fiber% 0 0 0 0.25 0.25 0.25 0.5 0.5 0.5x 62 68 69.5 69 71.5 73 68 71.5 74The plot below indicates some effect due to sand and fiber addition with no significantinteraction. This agrees with the statistical analysis in part b750.000.250.5070mean650 10 20 30Sand%320
Page 2:
Chapter 1: Overview and Descriptive
Page 6:
Page 10:
Page 16:
Page 20:
Page 24:
Page 28:
Page 32:
Page 36:
Page 40:
Page 44:
Page 48:
Page 52:
Page 56:
Page 62:
Page 66:
Page 70:
Page 74:
Page 78:
Page 82:
Page 86:
Page 90:
Page 94:
CHAPTER 2Section 2.11.a. S = { 1324
Page 98:
Chapter 2: Probability5.a.OutcomeNu
Page 102:
Chapter 2: Probability8.a. A 1 ∪
Page 106:
Chapter 2: Probability9.a. In the d
Page 110:
Chapter 2: Probabilityf. either (ne
Page 114:
Chapter 2: Probability17.a. The pro
Page 118:
Chapter 2: Probability24. Since A i
Page 122:
Chapter 2: ProbabilitySection 2.329
Page 126:
Chapter 2: Probability34.⎛20⎞
Page 130:
Chapter 2: Probabilityd. To examine
Page 134:
Chapter 2: Probability42. Seats:2
Page 138:
Chapter 2: Probability47.P(A ∩ B)
Page 142:
Chapter 2: ProbabilityP(M ∩ SS
Page 146:
Chapter 2: Probabilityc. P(all H’
Page 150:
Chapter 2: Probability61. P(0 def i
Page 154:
Chapter 2: Probability63.a.b. P(A
Page 158:
Chapter 2: Probability66. Define ev
Page 162:
Chapter 2: ProbabilitySection 2.568
Page 166:
Chapter 2: Probability79.Using the
Page 170:
Chapter 2: Probabilityd. P(passes i
Page 174:
Chapter 2: ProbabilitySupplementary
Page 178:
Chapter 2: Probability93.1a. There
Page 182:
Chapter 2: Probability101.a. The la
Page 186:
Chapter 2: Probabilityd. For what v
Page 190:
CHAPTER 3Section 3.11.S: FFF SFF FS
Page 194:
Chapter 3: Discrete Random Variable
Page 198:
Page 202:
Page 206:
Page 210:
Page 214:
Page 218:
Page 222:
Page 226:
Page 230:
Page 234:
Page 238:
Page 242:
Page 246:
Page 250:
Page 254:
Page 258:
CHAPTER 4Section 4.11.1∫ −∞11
Page 262:
Chapter 4: Continuous Random Variab
Page 266:
Page 270:
Page 274:
Page 278:
Page 282:
Page 286:
Page 290:
Page 294:
Page 298:
Page 302:
Page 306:
Page 310:
Page 314:
Page 318:
Page 322:
Page 326:
Page 330:
Page 334:
Page 338:
Page 342:
Page 346:
Page 350:
CHAPTER 5Section 5.11.a. P(X = 1, Y
Page 354:
Chapter 5: Joint Probability Distri
Page 358:
Page 362:
Page 366:
Page 370:
Page 374:
Page 378:
Page 382:
Page 386:
Page 390:
Page 394:
Page 398:
Page 402:
Page 406:
Page 410:
CHAPTER 6Section 6.11.a. We use the
Page 414:
Chapter 6: Point Estimation6.a. Let
Page 418:
Chapter 6: Point Estimation(.635)(.
Page 422:
Chapter 6: Point Estimation19.λ ,
Page 426:
Chapter 6: Point Estimation23. For
Page 430:
Chapter 6: Point Estimation29.a. Th
Page 434:
Chapter 6: Point Estimation35.xi+ x
Page 438:
CHAPTER 7Section 7.11.z implies tha
Page 442:
Chapter 7: Statistical Intervals Ba
Page 446:
Page 450:
Page 454:
Page 458:
Page 462:
Page 466:
Page 470:
Page 474:
CHAPTER 8Section 8.11.a. Yes. It is
Page 478:
Chapter 8: Tests of Hypotheses Base
Page 482:
Page 486:
Page 490:
Page 494:
Page 498:
Page 502:
Page 506:
Page 510:
Page 514:
Page 518:
Page 522:
CHAPTER 9Section 9.11.a. E ( X −
Page 526:
Chapter 9: Inferences Based on Two
Page 530:
Page 534:
Page 538:
Page 542:
Page 546:
Page 550:
Page 554:
Page 558:
50. Let = . 05Chapter 9: Inferences
Page 562:
Page 566:
Page 570:
Page 574:
Page 578:
78. Let µ1denote the true average
Page 582:
Page 586:
Page 590: CHAPTER 10Section 10.11.a. H o will
Page 594: Chapter 10: The Analysis of Varianc
Page 626: CHAPTER 11Section 11.11.30.659.27.6
Page 630: Chapter 11: Multifactor Analysis of
Page 692:
Chapter 11: Multifactor Analysis of
Page 696:
Page 700:
Page 704:
Chapter 12: Simple Linear Regressio
Page 708:
Page 712:
Page 716:
Page 720:
Page 724:
Page 728:
Page 732:
Page 736:
Page 740:
Page 744:
Page 748:
Page 752:
Page 756:
Page 760:
Page 764:
Page 768:
Page 772:
Page 776:
Page 780:
Page 784:
Page 788:
Chapter 13: Nonlinear and Multiple
Page 792:
Page 796:
Page 800:
Page 804:
Page 808:
Page 812:
Page 816:
Page 820:
Page 824:
Page 828:
Page 832:
Page 836:
Page 840:
Page 844:
Page 848:
Page 852:
Page 856:
Page 860:
Page 864:
Page 868:
Page 872:
Page 876:
Page 880:
Chapter 14: The Analysis of Categor
Page 884:
Page 888:
Page 892:
Page 896:
Page 900:
Page 904:
Page 908:
Page 912:
Page 916:
Chapter 15: Distribution-Free Proce
Page 920:
Page 924:
Page 928:
Page 932:
Page 936:
Page 940:
Chapter 16: Quality Control Methods
Page 944:
Page 948:
Page 952:
Page 956:
Page 960:
Page 964:
show all

chapter 1

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?