Studied by 38 people

5.0(2)

Get a hint

Hint

1

ANOVA

a statistical technique for testing differences in the means of several groups

New cards

2

one-way ANOVA

an analysis of variance wherein the groups are defined on only one independent variable

New cards

3

assumptions in order to do ANOVAs

populations are normally distributed

populations have homogenous variances

the individual observations are independent from one another, ie, one person's score doesn't influence another person's score

New cards

4

omnibus null hypothesis

the hypothesis that all population mean are equal

New cards

5

sum of squares (SS)

the sum of squared deviations around some point (usually around a mean or predicted value)

New cards

6

MS_between groups (MS_groups, MS_treatment):

variability among group means

New cards

7

MS_within (MS_error)

variability among subjects in the same treatment group

New cards

8

MS

mean square; SS/df

New cards

9

F statistic

the ratio of MS_group to MS_error, or MS_between to MS_within

New cards

10

η²

eta squared; SS_group/SS_total

New cards

11

ω²

omega squared

New cards

12

multiple comparison techniques

techniques for making comparisons between 2 or more group means subsequent to an analysis of variance

New cards

13

familywise error rate

the probability that a family of comparisons contains at least one type 1 error

we want to keep this down

New cards

14

3 of many post hoc procedures that control type 1 error

Protected t (fisher's least significant difference (LSD))

Bonferroni correction

Tukey procedure

New cards

15

protected t (fisher's least significant difference (LSD))

a technique in which we run t tests between pairs of means only if the analysis of variance was significant

New cards

16

bonferroni correction

a multiple comparison procedure in which the family-wise error rate is divided by the number of comparisons

divide α by the number of comparisons you want to make

New cards

17

tukey procedure

a multiple comparison procedure for making pairwise comparisons among means while holding the familywise error rate at α

New cards

18

factors

another word for IVs in the ANOVA

New cards

19

factorial design

an experimental design in which every level of one variable is paired with each level of one variable

New cards

20

two-way factorial design

an experimental design involving two IVs in which every level of one variable is paired with each level of one variable

New cards

21

two advantages of factorial designs over using multiple one-way ANOVAs

they allow us to look the interaction of variables

they allow us to use fewer participants without sacrificing power

New cards

22

interaction

a situation in a factorial design or contingency table in which the effects of one independent variable depend on the level of another independent variable

New cards

23

grand mean

the mean of all observations

New cards

24

main effect

the effect of one IV

New cards

25

simple effect

the effect of one IV at one level of another IV

New cards

26

between-subjects designs

designs in which different subjects serve under the different treatment levels

New cards

27

repeated-measures designs

experimental designs in which each subject receives all levels of at least one IV

New cards

28

within-subjects designs

experimental designs in which each participant produces multiple scores

New cards

29

assumptions of repeated-measures designs (are the same for any other F test)

normality in the distributions

homogeneity of variance

assumption of homogeneity of covariance: correlations among DV scores must be the same

New cards

30

advantages of repeated-measures designs

avoids the problem of person-to-person variability

controls for extraneous variables

requires fewer participants then between-subjects designs to have same amount of power

New cards

31

disadvantages of related samples

order effect

carry-over effect

New cards

32

order effect

the effect on performance attributable to the order in which treatments were administered

New cards

33

carry-over effect

the effect of previous trials (conditions) on a subject's performance on subsequent trials

New cards

34

counterbalancing

an arrangement of treatment conditions designed to balance out practice effects

New cards

35

chi-square test

a statistical test often used for categorical data

-dv is number of observations

-is non-parametric

New cards

36

one-classification variable

the chi-square goodness of fit test

New cards

37

goodness-of-fit test

a test for comparing observed frequencies with theoretically predicted frequencies

New cards

38

E

expected frequency

New cards

39

O

observed frequency

New cards

40

two classification variables

analysis of contingency tables using chi-square

New cards

41

contingency table

a two-dimensional table in which each observation is classified on the basis of two variables simultaneously

ex: Walsh tested the effectiveness of using antidepressants after treatment for anorexia nervosa

New cards

42

degrees of freedom for expected frequencies

(R-1)*(C-1)

New cards

43

chi square tests assume

independence of observations

New cards

44

you have independence if

one person's scores do not affect another person's scores

New cards

45

N

must equal the total of the rows, or the total of the columns

New cards

46

risk

number of occurrences on one event divided by total number of occurrences of events

New cards

47

risk ratio (relative risk)

ratio of two risks

New cards

48

odds

frequency of occurrence of one event divided by the frequency of occurrence of the other event

New cards

49

prospective study

a study in which you select participants on the basis of some current condition and follow them into the future

ex: if you're interested in the relationship between smoking and cancer, and you find people who smoke and then track over time who develops cancer

New cards

50

retrospective study

a study in which you select participants on some criterion and then look back at their behavior in the past

ex: if you study the relationship between smoking and cancer and you examine data that already exist in terms of who smoked and developed cancer

New cards

51

in a prospective study

you have to collect the data and analyze it

New cards

52

in a retrospective study

the data already exists and you just have to analyze it

New cards