chapter 1

More documents

Recommendations

Info

Chapter 16: Quality Control MethodsSupplementary ExercisesΣx i, x = 422. 31 , Σs i= 402 , s = 15. 4615 , Σ i= 1074r = 41.307739. n = 6, k = 26, = 10, 980( ) ( )3 15.4615 1−.952S chart: 15.4615 ±= 15.4615 ± 14.9141 ≈ .55,30.37.9523 (.848)( 41.31)R chart: 41 .31 ± = 41.31 ± 41.44 , so LCL = 0, UCL = 82.752.5363X( 15.4615)chart based on s : 422 .31 ± = 402.42,442.20.952 63( 41.3077)X chart based on r : 422 .31±= 402.36,442.262.536 62r ,40. A c chart is appropriate here. Σx i= 92 so 92 x = = 3. 833 , and24x ± 3 x = 3.833 ± 5.874 , giving LCL = 0 and UCL = 9.7. Because x 22 = 10 > UCL, theprocess appears to have been out of control at the time that the 22 nd plate was obtained.480
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 598:
Page 602:
Page 606:
Page 610:
Page 614:
Page 618:
Page 622:
Page 626:
CHAPTER 11Section 11.11.30.659.27.6
Page 630:
Chapter 11: Multifactor Analysis of
Page 634:
Page 638:
Page 642:
Page 646:
Page 650:
Page 654:
Page 658:
Page 662:
Page 666:
Page 670:
Page 674:
Page 678:
Page 682:
Page 686:
Page 690:
Page 694:
Page 698:
Page 702:
CHAPTER 12Section 12.11.a. Stem and
Page 706:
Chapter 12: Simple Linear Regressio
Page 710:
Page 714:
Page 718:
Page 722:
Page 726:
Page 730:
Page 734:
Page 738:
Page 742:
Page 746:
Page 750:
Page 754:
Page 758:
Page 762:
Page 766:
Page 770:
Page 774:
Page 778:
Page 782:
Page 786:
CHAPTER 13Section 13.11.2x and ∑
Page 790:
Chapter 13: Nonlinear and Multiple
Page 794:
Page 798:
Page 802:
Page 806:
Page 810:
Page 814:
Page 818:
Page 822:
Page 826:
Page 830:
Page 834:
Page 838:
Page 842:
Page 846:
Page 850:
Page 854:
Page 858:
Page 862:
Page 866:
Page 870:
Page 874:
Page 878:
CHAPTER 14Section 14.11.a. We rejec
Page 882:
Chapter 14: The Analysis of Categor
Page 886:
Page 890:
Page 894:
Page 898:
Page 902:
Page 906:
Page 910: Chapter 14: The Analysis of Categor
Page 914: CHAPTER 15Section 15.11. We test :
Page 918: Chapter 15: Distribution-Free Proce
Page 938: CHAPTER 16Section 16.11. All ten va
Page 942: Chapter 16: Quality Control Methods
show all

chapter 1

Create successful ePaper yourself

Delete template?

Save as template?