Statistical Methods for Psychology

Index 767

simple interaction effects, 451
simple main effects, 451
Simpson’s paradox, 157
simultaneous knowledge, 516
singular covariance, 528
size of an experimental effect, 343–348
d-family measures of effect size, 347–348
eta-squared (h^2 ), 344–345
omega-squared (v^2 ), 346–347
skewness, 27
slope, 254, 256
small expected frequencies, 151
software, 560
sources of variation, 327
sparse matrices, 644
Spearman’s correlation coefficient for ranked data (rs), 304
Spearman’s rho, 304
splines, 257
S-Plus (commercial software), 9
SPSS (commercial software), 9, 517, 593
square-root transformation, 340
SScells, 418
SSerror, 326
S-shaped curve, 563
SStotal, 326
SStreat, 326
standard deviation, 41–42
standard deviation as a measure of error, 258
standard error, 88, 183
alternative approaches to, 557
of beta, 556
of differences between means, 205
of estimate, 258, 259
and tests of regression coefficients, 529–530
standardization, 54
standardized regression coefficients, 257, 528–529
standard normal distribution, 71–72
using the tables of, 73–75
standard scores, 54, 79
standard set, 373
statistic, 5
statistical conclusions, 93–94
statistical software packages, 9, 560, 580
stem, 24
stem-and-leaf displays, 24–27
stepwise procedures, 548, 650–652
stepwise regression, 547, 549
Sternberg, Saul, 16
Stevens, S. S., 6
stratification, 621
structural equation modeling, 580
structural model, 320
structural models and expected mean squares, 420–421
Studentized range statistic (q), 389
Studentized residual, 542

Student’s tdistribution, 186

subjective probability, 113

success, 127

sufficiency, 45

sufficient statistic, 45

summary of the assumptions of chi-square, 152–153

summary table, 327

summation notation, 30–31

sum of squares, 324

sum of squares for contrasts, 372

sum of squares of y, 259

suppressor relationship, 548

suppressor variables, 538–539

symmetric and asymmetric models, 631

symmetric distribution, 27

symmetric relationships, 631

tabled chi-square distribution, 143–144

tables of standard normal distribution, 73–75

terminology and rules, 114–117

terms, 2–5

testing hypotheses about means, standard deviation

known, 183–185

testing models, 638–641

testing the difference between two independent bs, 273–274

testing the difference between two independent rs, 275

testing the difference between two

nonindependent rs, 277–278

testing the hypothesis that requals any specified

value, 275–276

testing the significance of b, 272–273

testing the significance of r, 271–272

testing the significance of r^2 , 533

testing the significance of , 298

test of significance, 373

test selection, 398

test statistics, 95

test statistics and their sampling distributions, 95

tetrachoric correlation coefficient, 303

the additive rule, 114–115

third quartile Q3, 39

three-way example, 645

three-way tables, 643–649

assumptions, 644

examining the saturated model, 647

hierarchical and nonhierarchical models, 644–645

possible models, 645–646

three-way example, 645

ties, 680–681

tolerance, 527

traditional approach to hypothesis testing, 91–92

trailing digits, 25

transformations, 336–343

the arcsine transformation, 341

logarithmic transformation, 338

r^2 pb