Six Sigma and Beyond: Statistics and Probability, Volume III
C
Canonical correlation, 154, 158
Cases
concordant, 77 “78
definition of, 18
discordant, 78
tied, 78 “79, 120
valid, 22
Causal models, 176 “180
CDF, see Cumulative distribution function (CDF)
Cells , 34, 236 “237
Central Limit Theorem (CLT), 45, 47, 266 “267
Central tendency, 30, 185 “186
Centroid, 130
CFI, 164
Characteristic root, 134
Characteristic vector, 134
Charts, see Plots
Chi-square
fit measure, 112 “114, 160 “161
in hypothesis-testing process, 65
likelihood -ratio, 160 “161
for measures of association, 73 “78, 81
in Monte Carlo simulation, 327
noncentrality measure, 161 “162
normed, 165
sample size , 161
Classification analysis, 109, 155 “156, 266 “267
CLT, 45, 47, 266 “267
Cluster analysis, 109, 155 “156, 266 “267
Cochran Q test, 115
Coding schemes, 16 “24
Coefficients
beta, 146
contingency, 75
correlation, see Correlation
eta, 80
normalized, 75
Pearson's r, 79 “80, 84 “88, 126 “127
phi, 75
Spearman rank, 127 “128
uncertainty, 80
Coincident indicator, 178 “179
Combinations, 226, 230
Comparative fit index (CFI), 164
Complementary events, 213 “214
Complementary set, 198
Concordant cases, 77 “78
Conditional probability, 209 “210
Confidence interval
as cumulative probability, 249
definition of, 48 “49
in regression, 96
size of, 51
Confirmatory factor analysis, 157
Conformability, 290
Conjoint analysis, 153 “154
Constant-elasticity multiplicative model, 178
Contingency coefficient, 75
Contingency table, 113
Continuity correction, 264 “265
Continuous distribution, 247
Continuous probability, 193
Continuous random variables , 245 “247
Control group , 13
Control variable, 83
Corner point, 299 “300
Correlation
assumptions for, 87
bivariate, 84
canonical, 154, 158
vs. chi-square test, 114
vs. covariance, 83 “84
cross-validation index for fit, 163
definition of, 84 “87
example of, 292 “293
Galton's rank order, 127
for linear dependence, 293
for measurement error check, 98
of multiple coefficients, 88 “89
one-tailed tests, 87
Pearson's r, 79 “80, 84 “88, 126 “127
in regression, 91 “97
RMSR for fit, 162
significance level, 87
spurious , 180
techniques for, 125 “126
two-tailed tests, 87
Correlogram, 172
Counting rules, 225 “226
Covariance
Box's M test, 142
cross-validation index for fit, 163
definition of, 83 “84
RMSR for fit, 162
Covariance structure analysis, 157
Cramer's V, 75
Cross-classification table, 34 “35, 73 “74
Cross-tabulation table, 34 “35, 73 “74
Cross-validation index, 162 “163
Cumulative distribution function (CDF)
vs. cumulative frequency function, 190 “191
definition of, 191 “192
discrete, 240 “243
in Kolmogorov-Smirnov test, 116
for normal distribution, 254 “259
of random variables, 245 “251
Cumulative frequency function, 190 “191