Statistics for the Behavioral Sciences by Frederick J. Gravetter, Larry B. Wallnau ISBN 10: 1305504917 ISBN 13: 9781305504912

Subject Index
A 3 B interaction, 456, 462
Abscissa, 42
Algebra, 637–639
Alpha level, 229–230, 238–239, 259
and type I errors, 237
Alternative hypothesis (H 1
), 228
American Psychological Association (APA),
77, 89
Analysis of regression, 540–541
F-ratios, 541–543
multiple regression, 549–550
Analysis of variance (ANOVA), 365–411
advantages of, 366, 370
assumptions for, 391–392
between-treatment variance, 372, 373
Chi-square test statistic and, 588–589
conceptual view of, 397–400
degrees of freedom, 379–381
effect size, 388–390, 408
F distribution table, 384–385
F-ratio, 373–374, 382
F-ratio, distribution of, 383–385
formulas, 376–377
hypothesis testing, 385–388
independent measures, 391–392
In the Literature, 389
logic of, 372–375
mean square (MS), 381–382, 400–401
notation, 375–376
pooled variance, 400–401
post hoc tests, 393–397
sample size, 390–391, 400
Scheffé test, 395–396
SPSS, 404–405
statistical hypotheses for, 369
statistics organizer, 712, 714
sum of squares (SS), 377–379
summary tables, 382
and t tests, 401–402
terminology in, 367–369
test statistic for, 370–371
Tukey’s HSD test, 394–395
Type I errors, 369–370, 393–394
unequal sample sizes, 390–391
within-treatment variance, 372–373
ANOVA. See Analysis of variance (ANOVA)
ANOVA formulas, 376–377
ANOVA summary tables, 382
Apparent limits, 41
Arithmetic average. See Means
Axes of a graph, 42
Bar graphs, 44–45, 90–91
SPSS, 59
two-factor ANOVA, 455
Base, 640
Best fitting line, 533
Beta, 238
Between-subjects research design, 301. See
also Analysis of variance (ANOVA);
Independent-measures t test;
Two-factor ANOVA
Between-subjects sum of squares,
422–423
Between-subjects variance, 420
Between-treatments degrees of freedom
(df between
), 380–381
Between-treatments sum of squares. See
SS between treatments
Between-treatments variance, 372, 373,
417–418, 420
two-factor ANOVA, 460–461
Biased statistics, 112, 117–119
Bimodal distributions, 84
Binomial data, 604
Binomial distribution, 179–183, 188–189,
606, 610
normal approximation to, 181–183, 606,
610–611
Binomial test, 603–623
assumptions for, 612
data for, 606
defined, 605
example of, 608–609
and goodness of fit test, 612–614
hypotheses for, 605–606
In the Literature, 611
notation, 605
score boundaries and, 610–611
sign test, 614–617
SPSS, 618
statistics organizer, 706
test statistic for, 606–607
Binomial variables, 516
Body of the normal curve, 168, 169, 647
Categories, measurement, 35
Causation, 497–498
Cell of a matrix, 449
Central limit theorem, 202
distribution of sample means, 199–200
Central tendency, 67–98, 530
computing, 96
defined, 69
In the Literature, 89
means. See Means
medians. See Medians
modes, 83–85, 88–89
purpose, 68
selecting a measure, 86–89
skewed distributions, 93
SPSS, 95
symmetrical distributions, 92–93
Chi (χ), 562
Chi-square distribution, 567–569, 659
Chi-square test, 12
Chi-square test for goodness of fit, 562.
See also Goodness of fit test
Chi-square test for independence, 574.
See also Independence test using
Chi-square statistic
Chi-square test statistic, 559–601
and ANOVA, 588–589
Cohen’s w, 582–584
Cramér’s V, 584–586
degrees of freedom, 567–569, 578–579
effect size, 583, 584
goodness of fit test, 561–573
independence test using Chi-square
statistic, 573–582
and the independent-measures t test,
588–589
In the Literature, 572
median test, 589–591
nonparametric tests, 561–562,
587–588
phi-coefficient, 584–586
special applications of, 587–591
SPSS, 593–594
Child Manifest Anxiety Scale, 296
Class intervals, 39
Cloud pattern, 224
Coefficient of determination (r 2 ), 500–501,
540–541
effect size, 516–518
Cohen’s d
effect size, 251–254, 263, 294
independent-measures design, 316–317,
329
repeated-measures design, 347
t statistic, 279–281
Cohen’s w, 582–584
Computer software. See SPSS (Statistical
Package for the Social Sciences)
725