Introduction to Probability and Statistics for Engineers and Scientists

(Sean Pound) #1

Index 623


Range of data, 27
Rank sum test
classical approximation, 529–531
null hypothesis, 526
simulation, 531–533
Tstatistic, 525–529
Rayleigh density function, 583
Regression coefficients
definition, 352
statistical inferences concerning regression
parameters


a, 370
b, 362–370
mean response, 371–373
prediction intervals of future response,
373–375
Regression fallacy, 370
Regression to the mean, 366–370
Relative frequency, 10, 12, 15
Residuals in regression, 358
model assessment, 378–380
standardized residuals, 379
sum of squares
chi-square distribution, 358–359
computational identity, 360–362
multiple linear regression, 397, 402–403
Robust test, 305
Row sum of squares, 460–461
Runs test, 533–536


S


Sample, 3, 201–202
Sample correlation coefficient
coefficient of determination relationship, 378
definition, 36
positive versus negative correlations, 36
properties, 37–40
Sample mean
analysis of variance for multiple comparisons
of sample means, 450–452
approximate distribution, 210–212
definition, 17, 19, 202–203
distribution from a normal population, 215


joint distribution with sample variance,
215–217
probability density function, 203
Sample median, 20–21
Sample mode, 21
Sample percentile
definition, 25
quartiles, 25–27
Sample space
definition, 56
spaces having equally likely outcomes, 61–67
Sample standard deviation, 24, 213
Sample variance
algebraic identity for computation, 23–24
definition, 22–23, 213–214
joint distribution with sample mean, 215–217
Scatter diagram, 34, 352
S-control charts, 554
Sequence of interarrival times, 181
Shockley equation, 162
Signed rank test, 519–525
Significance level, 293, 306, 309
Sign test, 515–519
Simple hypothesis, 292
Simple regression equation, 352
Skewed data set, 31
Standard deviation,seeSample standard
deviation; Variance
Standard normal distribution function, 170–171,
175, 612
Standardized residuals, 379
Statistic, 202
Statistical hypothesis test
Bernoulli populations, 323–330
composite hypothesis, 292
definition, 291
equality of normal variances, 321–323
equality of two normal means
known variances, 312–314
pairedt-test, 319–320
unknown and unequal variances, 318
unknown variances, 314–318
level of significance, 293
normal population mean with known
variance, 293–305
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