Applied Statistics Using SPSS, STATISTICA, MATLAB and R

More documents

Recommendations

Info

Contents xiii E.26 Soil Pollution ..........................................................................................482 E.27 Stars ........................................................................................................482 E.28 Stock Exchange.......................................................................................483 E.29 VCG........................................................................................................484 E.30 Wave .......................................................................................................484 E.31 Weather...................................................................................................484 E.32 Wines ......................................................................................................485 Appendix F - Tools 487 F.1 <strong>MATLAB</strong> Functions...............................................................................487 F.2 R Functions .............................................................................................488 F.3 Tools EXCEL File ..................................................................................489 F.4 SCSize Program......................................................................................489 References 491 Index 499
Page 2: Applied Statistics Using SPSS, STAT
Page 6: E d itors Prof. Dr. Joaquim P. Marq
Page 10: Contents Preface to the Second Edit
Page 14: Contents ix 5.2.3 The Chi-Square Te
Page 18: Contents xi Appendix A - Short Surv
Page 24: Preface to the Second Edition Four
Page 28: xviii Preface to the First Edition
Page 32: xx Symbols and Abbreviations ]a, b[
Page 36: xxii Symbols and Abbreviations Nµ,
Page 40: xxiv Symbols and Abbreviations SST
Page 44: 2 1 Introduction In the case of the
Page 48: 4 1 Introduction precision of the r
Page 52: 6 1 Introduction randomly drawn sam
Page 56: 8 1 Introduction This can be done,
Page 60: 10 1 Introduction Several statistic
Page 64: 12 1 Introduction 1 0.8 0.6 0.4 0.2
Page 68: 14 1 Introduction example) and on a
Page 72:
16 1 Introduction Imagine then that
Page 76:
18 1 Introduction population of oth
Page 80:
20 1 Introduction perform menu oper
Page 84:
22 1 Introduction Graphs: Operation
Page 88:
24 1 Introduction >> c(1,2)={‘T80
Page 92:
26 1 Introduction > x [1] 1 2 3 4 5
Page 96:
28 1 Introduction Figure 1.13. A pa
Page 100:
30 2 Presenting and Summarising the
Page 104:
Page 108:
Page 112:
Page 116:
Page 120:
Page 124:
Page 128:
Page 132:
Page 136:
Page 140:
Page 144:
Page 148:
Page 152:
Page 156:
Page 160:
Page 164:
Page 168:
Page 172:
Page 176:
Page 180:
Page 184:
Page 188:
Page 192:
Page 196:
Page 200:
Page 204:
82 3 Estimating Data Parameters los
Page 208:
84 3 Estimating Data Parameters w
Page 212:
86 3 Estimating Data Parameters int
Page 216:
88 3 Estimating Data Parameters app
Page 220:
90 3 Estimating Data Parameters m =
Page 224:
92 3 Estimating Data Parameters In
Page 228:
94 3 Estimating Data Parameters The
Page 232:
96 3 Estimating Data Parameters est
Page 236:
98 3 Estimating Data Parameters Exa
Page 240:
100 3 Estimating Data Parameters Th
Page 244:
102 3 Estimating Data Parameters A:
Page 248:
104 3 Estimating Data Parameters A:
Page 252:
106 3 Estimating Data Parameters We
Page 256:
108 3 Estimating Data Parameters 3.
Page 260:
4 Parametric Tests of Hypotheses In
Page 264:
4.1 Hypothesis Test Procedure 113 V
Page 268:
p B X 4.2 Test Errors and Test Powe
Page 272:
xα = µ B −1 . 64× σ = 1300
Page 276:
4.2 Test Errors and Test Power 119
Page 280:
4.3 Inference on One Population 121
Page 284:
Example 4.1 4.3 Inference on One Po
Page 288:
4.3 Inference on One Population 125
Page 292:
4.4 Inference on Two Populations 12
Page 296:
Page 300:
Page 304:
Page 308:
Then, the following test statistic:
Page 312:
Page 316:
Page 320:
4.5 Inference on More than Two Popu
Page 324:
4.5.2 One-Way ANOVA 4.5.2.1 Test Pr
Page 328:
145 The ANOVA test uses precisely t
Page 332:
4.5 Inference on More than Two Popu
Page 336:
149 transformation. Notice how the
Page 340:
4.5.2.2 Post Hoc Comparisons 151 Fr
Page 344:
{CON, ADI, FAD, GLA}; {ADI, FAD, GL
Page 348:
155 in the values of the sample mea
Page 352:
SST = c i= 1 j= 1 = r ∑∑ c ∑
Page 356:
159 Sum of the squares representing
Page 360:
161 Notice that in Table 4.21 the t
Page 364:
163 c. The comparison between hospi
Page 368:
Power 1.00 .95 .90 .85 2-Way (2 X 3
Page 372:
Exercises 167 4.5 Consider the Prog
Page 376:
Exercises 169 freshmen in a program
Page 380:
172 5 Non-Parametric Tests of Hypot
Page 384:
Page 388:
Page 392:
Page 396:
Page 400:
Page 404:
Page 408:
Page 412:
Page 416:
Page 420:
Page 424:
Page 428:
Page 432:
Page 436:
Page 440:
Page 444:
Page 448:
Page 452:
Page 456:
Page 460:
Page 464:
Page 468:
Page 472:
Page 476:
Page 480:
Page 484:
224 6 Statistical Classification (c
Page 488:
226 6 Statistical Classification Eq
Page 492:
228 6 Statistical Classification
Page 496:
230 6 Statistical Classification li
Page 500:
232 6 Statistical Classification It
Page 504:
234 6 Statistical Classification ve
Page 508:
236 6 Statistical Classification Fi
Page 512:
238 6 Statistical Classification ω
Page 516:
240 6 Statistical Classification ω
Page 520:
242 6 Statistical Classification th
Page 524:
244 6 Statistical Classification Fi
Page 528:
246 6 Statistical Classification Bo
Page 532:
248 6 Statistical Classification We
Page 536:
250 6 Statistical Classification Th
Page 540:
252 6 Statistical Classification si
Page 544:
254 6 Statistical Classification In
Page 548:
256 6 Statistical Classification St
Page 552:
258 6 Statistical Classification St
Page 556:
260 6 Statistical Classification At
Page 560:
262 6 Statistical Classification pe
Page 564:
264 6 Statistical Classification i(
Page 568:
266 6 Statistical Classification ap
Page 572:
268 6 Statistical Classification Co
Page 576:
270 6 Statistical Classification 6.
Page 580:
272 7 Data Regression Correlation d
Page 584:
274 7 Data Regression These propert
Page 588:
276 7 Data Regression The total var
Page 592:
278 7 Data Regression Next, we crea
Page 596:
280 7 Data Regression b 1 = ∑ ( x
Page 600:
282 7 Data Regression Example 7.5 Q
Page 604:
284 7 Data Regression The sampling
Page 608:
286 7 Data Regression From the defi
Page 612:
288 7 Data Regression * SSLF SSPE M
Page 616:
290 7 Data Regression where: - y is
Page 620:
292 7 Data Regression 1.0000 0.9692
Page 624:
294 7 Data Regression The first lin
Page 628:
296 7 Data Regression 7.2.5 ANOVA a
Page 632:
298 7 Data Regression must ask whic
Page 636:
300 7 Data Regression model. Simila
Page 640:
302 7 Data Regression The MATLAB po
Page 644:
304 7 Data Regression the same way
Page 648:
306 7 Data Regression 7.3.2 Evaluat
Page 652:
308 7 Data Regression The MATLAB re
Page 656:
310 7 Data Regression with s 2 =
Page 660:
312 7 Data Regression the threshold
Page 664:
314 7 Data Regression 7.11, the lar
Page 668:
316 7 Data Regression determination
Page 672:
318 7 Data Regression smaller discr
Page 676:
320 7 Data Regression Besides its u
Page 680:
322 7 Data Regression VIF and Mean
Page 684:
324 7 Data Regression Taking the na
Page 688:
326 7 Data Regression Example 7.22
Page 692:
328 7 Data Regression possible to p
Page 696:
330 8 Data Structure Analysis In Fi
Page 700:
332 8 Data Structure Analysis of th
Page 704:
334 8 Data Structure Analysis 2 −
Page 708:
336 8 Data Structure Analysis using
Page 712:
338 8 Data Structure Analysis ∑
Page 716:
340 8 Data Structure Analysis We se
Page 720:
342 8 Data Structure Analysis p = 0
Page 724:
344 8 Data Structure Analysis In or
Page 728:
346 8 Data Structure Analysis A: On
Page 732:
348 8 Data Structure Analysis ⎡0.
Page 736:
350 8 Data Structure Analysis 1 0 -
Page 740:
352 8 Data Structure Analysis 8.9 C
Page 744:
354 9 Survival Analysis P( t ≤ T
Page 748:
356 9 Survival Analysis Example 9.2
Page 752:
358 9 Survival Analysis the Fatigue
Page 756:
360 9 Survival Analysis “death”
Page 760:
362 9 Survival Analysis A: The Hear
Page 764:
364 9 Survival Analysis From Figure
Page 768:
366 9 Survival Analysis denominator
Page 772:
368 9 Survival Analysis The exponen
Page 776:
370 9 Survival Analysis γ This is
Page 780:
372 9 Survival Analysis the proport
Page 784:
374 9 Survival Analysis 9.5 Compute
Page 788:
376 10 Directional Data Example 10.
Page 792:
Page 796:
380 10 Directional Data The MATLAB
Page 800:
382 10 Directional Data A: We use t
Page 804:
384 10 Directional Data For p = 2,
Page 808:
386 10 Directional Data Thus, the r
Page 812:
388 10 Directional Data from a unif
Page 816:
390 10 Directional Data * 2 z = ( 1
Page 820:
392 10 Directional Data 10.4.3 The
Page 824:
Page 828:
396 10 Directional Data 10.5.2 Mean
Page 832:
398 10 Directional Data Similar res
Page 836:
400 10 Directional Data Exercises 1
Page 840:
Appendix A - Short Survey on Probab
Page 844:
A.1 Basic Notions 405 corresponding
Page 848:
A.2 Conditional Probability and Ind
Page 852:
A. 4 Bayes ’ Theorem 409 The firs
Page 856:
A.5 Random Variables and Distributi
Page 860:
a 0.5 0.4 0.3 0.2 0.1 0 f (x ) a a+
Page 864:
Example A. 12 A.6 Expectation, Vari
Page 868:
n [ X ] = ∑ i= 1 A.6 Expectation,
Page 872:
A.7 The Binomial and Normal Distrib
Page 876:
A.7 The Binomial and Normal Distrib
Page 880:
The following results are worth men
Page 884:
A.8.2 Moments A.8 Multivariate Dist
Page 888:
For the d-variate case, this genera
Page 892:
0.25 0.2 0.15 0.1 0.05 p(x) A.8 Mul
Page 896:
432 Appendix B - Distributions A: T
Page 900:
Page 904:
436 Appendix B - Distributions For
Page 908:
Page 912:
440 Appendix B - Distributions Dist
Page 916:
442 Appendix B - Distributions 0.45
Page 920:
444 Appendix B - Distributions B.2.
Page 924:
Page 928:
448 Appendix B - Distributions B.2.
Page 932:
450 Appendix B - Distributions Dist
Page 936:
452 Appendix B - Distributions 1 0.
Page 940:
Page 944:
456 Appendix C - Point Estimation T
Page 948:
458 Appendix C - Point Estimation
Page 952:
460 Appendix D - Tables p n k 0.05
Page 956:
Page 960:
Page 964:
466 Appendix D - Tables D.3 Student
Page 968:
468 Appendix D - Tables D.5 Critica
Page 972:
470 Appendix E - Datasets The varia
Page 976:
472 Appendix E - Datasets E.6 CTG T
Page 980:
474 Appendix E - Datasets E.9 FHR T
Page 984:
476 Appendix E - Datasets E.14 Fore
Page 988:
478 Appendix E - Datasets DATE_REOP
Page 992:
480 Appendix E - Datasets CG: Conic
Page 996:
482 Appendix E - Datasets E.26 Soil
Page 1000:
484 Appendix E - Datasets E.29 VCG
Page 1004:
Appendix F - Tools F.1 MATLAB Funct
Page 1008:
Appendix F - Tools 489 r
Page 1012:
References Chapters 1 and 2 Anderso
Page 1016:
References 493 Gardner MJ, Altman D
Page 1020:
References 495 Raudys S, Pikelis V
Page 1024:
References 497 Mardia KV, Jupp PE (
Page 1028:
500 Index 5.9 (two paired samples t
Page 1032:
502 Index H hazard function, 353 ha
Page 1036:
504 Index S sample, 5 mean, 416 siz
show all

Applied Statistics Using SPSS, STATISTICA, MATLAB and R

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

Delete template?

Save as template?