620 Index
Histogram
bimodal data set, 33–34
definition, 16
normal data set, 31
Hotel, D. G., 21
Hypergeometric random variable, 156–157
binomial random variable relationship,
159–160, 219–220
mean, 157
variance, 157–158
Hypothesis test,seeStatistical hypothesis test
I
Independent events, 76–80
Independent random variables, 101–105
Independent variable, 351
Indicator random variable, 90–91
expectation, 109
variance, 120
Inferential statistics, 2–3
Information theory, entropy, 108
Interaction of row and column in analysis of
variance, 464
Interval estimates, 240
J
Joint distribution, sample mean and sample
variance in normal population,
215–217
Jointly continous random variables, 99
Jointly distributed random variables, 95–101
Joint probability density function, 99–100
Joint probability mass function, 96
K
Kolmogorov’s law of fragmentation, 237–238
Kolmogorov–Smirnov goodness of fit test,
504–508
Kolmogorov–Smirnov test statistic, 504–507
L
Laplace, P., 5
Least squares estimators in linear regression
distribution of estimators, 355–362
estimated regression line, 354
mean and variance computation, 356–357
multiple linear regression, 394–405
normal equations, 353–354
notation, 360
sum of squared differences, 353
weighted least squares, 384–390
Left-end inclusion convention, 15
Life testing
exponential distribution
Bayesian appproach, 596–598
sequential testing, 590–594
simultaneus testing, 584–590, 594
hazard rate functions, 581–584
maximum likelihood estimator of life
distributions, 238–240
Likelihood function, 230
parameter estimation by least squares,
602–604
two-sample problem, 598–600
Weibull distribution, 600–602
Linear regression equation, 351–352
Linear transformation, 381–384
Line graph, 10
Logistic regression model, 410–413
Logistics regression function, 410
Logistics distribution, 192–193
Logit, 411
Lower control limit, 547–548, 552–553,
555–559, 562M
Mann-Whitney test, 525
Marginal probability mass function, 98
Markov’s inequality, 127–129
Maximum likelihood estimator
of Bernoulli parameter, 231–233
definition, 230–231
Kolmogorov’s law of fragmentation, 237–238
of life distributions, 238–240
of normal population, 236–238
of Poisson parameter, 234–235
of uniform distribution, 238
Mean,seeSample mean