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| Ïîèñê ïî óêàçàòåëÿì |
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| Stone C.J.D. — Course in Probability and Statistics |
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| Ïðåäìåòíûé óêàçàòåëü |
Negative multinomial distribution 194
Nelder, J.A. 681
Newton — Raphson method 712 717
Neyman — Pearson lemma 656
Neyman, Jerzy 407
Nominal confidence bound 642 729
Nominal confidence interval 642 729
Nonadditive function 417
Nonidentifiable space 405 438
Nonidentifiable space, least-squares approximation in 483
Nonidentifiable space, least-squares estimate in 496
Nonidentifiable space, maximum-likelihood estimation in 700
Nonnegative, integer-valued random variable distribution function and quantiles 55—58
Nonnegativity of distribution 14
Nonsingular matrix 444
Nontrivial linear parameter 356 521
Nonzero function 427
Norm 456 495
Normal approximation 149 767
Normal approximation to binomial distribution 179—186
Normal approximation to gamma distribution 156—157
Normal approximation to Poisson distribution 202
Normal approximation with half-integer correction 180—181
Normal approximation, central limit theorem and 158
Normal distribution 145—155 766—767.
Normal distribution, defined 148
Normal distribution, density function 148
Normal distribution, distribution function 148
Normal distribution, mean 148
Normal distribution, multivariate 263—273
Normal distribution, quantiles 148
Normal distribution, standard deviation 148
Normal distribution, variance 148
Normal equations 485—493 497—504
Normal equations, defined 485
Normal equations, matrix form 486 501
Normal equations, system of 485 498
Normal linear regression model with random inputs 422
Normal linear regression model, conditional form of 422
Normal linear regression model, defined 419
Normal linear regression model, experimental version 421
Normal linear regression model, linear parameters of 520—521
Normal linear regression model, normal one-sample and multisample models as 421—422 526 553—555
Normal multisample model 354—357 776—777
Normal multisample model as normal linear regression model 421—422 526 553—555
Normal one-sample model 353 54 515—516 776
Normal one-sample model as normal linear regression model 421—422 515—516
Normal regression model 419
Normal regression model, experimental version 420
Normalizing function 663
Null hypothesis 366
Odds 53
Odds ratio 638
One-sample model 421—422
One-sample model, normal 353—354 515—516
Order statistics 178
Ordered pair 7
Ordered pair, random 29
Orthogonal array 579—634
Orthogonal array, defined 586
Orthogonal basis 461
Orthogonal complement 580
Orthogonal components 580
Orthogonal functions 457
Orthogonal linear spaces 579
Orthogonal linear spaces, direct sum of 579
Orthogonal projection 470—484
Orthogonal projection, defined 471
Orthonormal basis 461
Orthonormal functions 458
p-value 342 371 376 553 576 643 669 737 742
P-value, exact 651—661
Pairing 385
Pairwise independent random variables 583
Parallel, components m 75
Parallelogram law 467
Parameter, inverse-scale 204
Parameter, location 63
Parameter, random 330—337
Parameter, scale 63
Partition 6
Partitioned matrix 758—759
Percentiles 46
Permutation 165
Pilot plant experiment 407—409 603—608
playing cards 294
Poisson approximation 200—201
Poisson distribution 195—203 769
Poisson distribution as exponential family 662—663
Poisson distribution, defined 195
Poisson distribution, exact P-values and 660
Poisson distribution, mean 195
Poisson distribution, modes 198
Poisson distribution, normal approximation to 202
Poisson distribution, probability function 195 198
Poisson distribution, second moment 196
Poisson distribution, standard deviation 195—196
Poisson distribution, variance 195—196
Poisson one-sample and multisample models 636 786—787
Poisson process 204—208
Poisson process, defined 205
Poisson regression 673—750
Poisson regression function 677
Poisson regression model 677
Poisson regression model, linear 677
Polar coordinates 260—261
Polya's urn scheme 291
Polymer experiment 396—406 502—504
Polymer experiment, data 396—397
Polynomial 429
Pooled estimate of variance 355
Posterior density function 331
Posterior distribution 331
Power 341
Power transformation 65—68
Power, Neyman — Pearson lemma and 656—658
Power, off test 377—378
Prediction 316—322
Prediction, linear 213—215
Prediction, mean squared error of 213
Prediction, multiple linear 236—242
Predictor 213
Predictor, best 214 317
Predictor, error of 213
Predictor, linear 214 236—242
Predictor, mean squared error of 213
Predictor, root mean squared error of 214
Prior distribution 331
Prior distribution, subjective 334—335
probability 12 14
Probability function 33—38 761
Probability function, conditional 283—284
Probability function, defined 33
Probability function, design 582
Probability function, joint 189
Probability function, marginal 331
Probability function, mode of 176
Probability measure 20
Probability theory 1
Probability, conditional 275
Probability, subjective 3
Proper subset 5
Proper subspace 433
Pseudorandom numbers 126
Pythagorean Theorem 457
Quantile function 46
Quantiles 762—763. See also Appendix E
Quantiles for continuous random variable 46—55
Quantiles for nonnegative, integer-valued random variable 55—58
Quartiles 46
| Random inputs 422—423 681—682
random matrix 219
Random matrix, expectation of 219
Random ordered pair 29
Random parameters 330—337
Random sample 112 765—766
Random variables 23
Random variables, artificial 582
Random variables, bounded 96
Random variables, constant 33
Random variables, continuous 38
Random variables, correlated 217
Random variables, dependent 70
Random variables, design 582
Random variables, discrete 33
Random variables, independent 70
Random variables, indicator 35
Random variables, integer-valued 24
Random variables, positive 24
Random variables, real-valued 24
Random variables, sequences of 77—78
Random variables, standardized 105
Random variables, transformations of 29—32
Random variables, uncorrected 217
Random vector 219
Random vector, expectation of 219
Randomization 380 620—634
Randomized complete block design 623
Rate 205
Rate function 677
Rate, relative 669
Regression 314
Regression coefficients 416 671
Regression function 302 675
Regression function, additive 417
Regression function, least-squares approximation to 474
Regression function, least-squares estimate of 474 495—496
Regression model 415
Regression model, experimental version 419
Regression model, heteroskedastic 419
Regression model, homoskedastic 419
Regression model, homoskedastic linear 419
Regression model, linear 415
Regression model, normal 419
Regression model, normal linear 419
Regression to the mean 314
Rejection region 340 366—367
Relative frequencies 2 10
Relative frequencies, law of 12—13
Relative frequency interpretation 2
Relative root mean squared error 216
Reliability 59
Repetitions 412
Residual 397 423
Residual sum of squares (RSS) 397 423—424 495 497
Response variable 324 411 675
Restriction 442
Risk 638
Risk function 675
Risk, relative 638
Rolle's theorem 446
Root mean squared error 214
Roulette 18—19
Run 412
Sample correlation 383
Sample covariance 383
Sample distribution 5—14
Sample distribution, defined 10
Sample standard deviation 116
Sample variance 116—118 353 357 513
Sample variance, defined 116
Sample variance, variance vs. 118
Sampling with replacement 17—18 73 185 289—290
Sampling without replacement 17—18 73 185 285—300
Sampling without replacement, means, variances, and covariances under 287—290
Saturated models 784—785 793
Saturated models, maximum likelihood estimation for 692—697
Saturated space 405 447—454 585
Saturated space, defined 448
Scale invariant 108
Scale parameter 63
Schwarz inequality 215 456
Screening experiment 590
Second moment 99
Seed 126
Sequence of independent random variables 77—78
Series, components in 74
Set function 4
Set theory, notation and terminology of 5—8
Sign test 659
Simple experiment 9
Simulation 121—133 630—632
Singular matrix 444
Size of set 3 15
Size of test 341—343
Sleeping drug experiment 378—385
span 429
Spurious effect 326
Squared error of prediction 213
Squared multiple correlation coefficient 241 508
Squared multiple correlation coefficient, adjusted 578
Squared norm 456 495
Standard Cauchy distribution 51
Standard Cauchy distribution as t distribution 347
Standard Cauchy distribution, density function 50
Standard Cauchy distribution, distribution function 51
Standard Cauchy distribution, mean 89—90
Standard Cauchy distribution, quantiles 51
Standard Cauchy distribution, variance 109
Standard deviation 100
Standard error 118—119 355 357 521 641 666 726
Standard logistic distribution 53
Standard logistic distribution, density function 52
Standard logistic distribution, distribution function 52
Standard logistic distribution, mean 95
Standard logistic distribution, quantiles 52
Standard logistic distribution, variance 109
Standard normal distribution 146
Standard normal distribution, chi-square and 344—345
Standard normal distribution, density function 145
Standard normal distribution, distribution function 146 828
Standard normal distribution, mean 147
Standard normal distribution, mode 146
Standard normal distribution, quantiles 147
Standard normal distribution, second moment 147
Standard normal distribution, standard deviation 147
Standard normal distribution, variance 147
Standard normal random variables, Box — Mueller generation of 261—262
Standardized random variable 105
Statistic 116
Statistical Design and Analysis of Experiments (John) 409
Statistical Methods in Engineering and Quality Assurance (John) 396
Statistics for Experimenters (Box, Hunter and Hunter) 407 605
Step-halving 712
Stepwise addition and deletion 558
Stirling's formula 135
Stratification 290
Strong Law of Large Numbers 113
Student's t distribution 347
Subjective priors 334—335
Subjective probability 3
Submodel 560—568
Subset 5
Subset, proper 5
subspace 433
Subspace, orthogonal projection onto 479—483
Subspace, proper 433
Subspace, submodel and 560—568
Sugar beet experiment 407—408 526—537 597 620—634
Sugar beet experiment, data 360 407—408
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