Pascal dist ribution, see N egative binomia l
distribution
Poisson distribution, 173–176, 184
mean, 176, 184
table, 367
variance, 176, 184
Population, 259
Probability, 13
assignment, 16, 17
conditional,20–21
function, 13
measure, 13
Probability density function (pdf), 44–46
conditional,62–63
joint (jpdf), 49–51
marginal, 57
Probability distribution function (PD F ), 39–41
bivariate, 49
conditional, 61
joint (JPD F ), 49–51
marginal, 50
mixed-type, 46
Probability mass function (pmf), 41, 43
conditional, 61
joint (jpmf), 51–55
marginal, 52
Random experiment, 12
R a ndom sa mple, see Sa mple
Random variable,37–39
continuous, 38
discrete, 38
function of, 120
sum of, 145
Random vector
Random walk, 52
Range space, 120
R egression coefficient, 336
confidence interval, 347
least-square estimate, 344
test of hypothesis, 316
Relative likelihood,16–17
R eliability, 60, 218
Residual, 337
Return period, 169
Sample, 259
size, 260
value, 260
Sample mean, 97, 261
mean, 261
variance, 261
Sample moment, 263–264
Sample point, 12
Sample space, 12
Sample variance, 262–263
mean, 262
variance, 262
Schwarz inequality, 92
Set, 8–12
complement of, 9
countable (enumerable), 8
disjoint, 10
element, 8
empty, 9
finite, 8
infinite, 8
subset of, 8
uncountable (nonenumerable), 8
Set operation, 9–12
difference, 10
intersection (product), 10
union (sum), 9
Significance level, 319
Spreadsheet, 3
Standard deviation, 79–81
Statistic, 260
sufficient, 275
St atistica l independence, see
Independence
Sterling’s formula, 107
St u d en t ’s t - d ist r ib u t io n , 298–299
table, 370
Sum of random variables, 93,
145–146
characteristic function, 104–105
moment, 94
probability distribution, 106, 146
Test of hypothesis, 316
Total probability theorem, 23
Tree diagram, 27–28
Unbiasedness, 265
U niform distribution, 57, 189, 236
bivariate, 193
mean, 192, 236
variance, 192, 236
Unimodal distribution, 79
Variance, 79, 82
Venn diagram, 9
Weibull distribution, 235
Subject Index 391