Brainscape's Knowledge GenomeTM


Top Flashcards (Certified)
All Flashcards

Research Comps > Statistical Analyses > Flashcards

Statistical Analyses Flashcards

(56 cards)

Start Studying
1
Q

Pearson Correlation

A

Used to determine the extent of the linear relationship between 2 variables

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

How many IVs and DVs with a Pearson Correlation

A

0 IV
0 DV
Instead, 2+ variables (measured on the same people)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Independent Groups t-test

A

determines relationship between an IV with 2 levels and a DV with interval characteristics

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Independent Groups t-test # of IVs and DVs

A

1 IV - between subjects, 2 levels

1 DV - interval characteristics

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Correlational Groups t-test

A

determines relationship between an IV with 2 levels and a DV with interval characteristics

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Correlational Groups t-test # of IVs and DVs

A

1 IV - within subjects, 2 levels

1 DV - interval characteristics

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

One-way ANOVA

A

determine a relationship between IV with more than 2 levels and a DV

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

One-way ANOVA # of IVs and DVs

A

1 IV - between subjects, 3 or less levels

1 DV - interval characteristics

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

One-way repeated-subjects ANOVA

A

determine relationship between IV with 3 or less levels and DV but single group receives all conditions of interest

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

one-way repeated-subjects ANOVA # of IVs and DVs

A

1 IV - within subjects, 3 or less levels

1 DV - interval characteristics

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Tukey HSD test

A

post-hoc test used after null hypothesis has been rejected to determine the nature of the relationship between variables
(planned contrast is considered more appropriate)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Two-way (factorial) between-subjects ANOVA

A

involves 1 DV and 2 or more IVs with 2 or more levels

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Two-way (factorial) between-subjects ANOVA # of IVs and DVs

A

IVs - 2 or less, between subjects

DV - 1, interval characteristics

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Two-way (factorial) repeated measures ANOVA

A

involves 1 DV and 2 or more IVs with 2 or more levels but single group receives all conditions of interest

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Two-way (factorial) repeated measures ANOVA

A

IVs - 2 or less, within subjects with 2 or less levels

DVs - 1, interval characteristics, variables

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

One-way between subjects ANCOVA

A

assess the influence of 1 IV on 1 DV after effects of 1 or more covariates have been removed

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

One-way between subjects ANCOVA # of IVs and DVs

A

IVs - 1, 2 or less between subjects
DVs - 1, interval characteristics
Covariate - 1 or more

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

One-way repeated measures ANCOVA

A

assess the influence of 1 IV on 1 DV after the effects of covariates is removed

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

One-way repeated measures ANCOVA # of IVs and DVs

A

IVs - 1, within subjects, 2 or less levels
DVs - 1, interval characteristics
Covariates - 1 or more

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

Two-way (factorial) between-subjects ANCOVA

A

assess influence of 1 IV on 1 DV after effects of covariates removed

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

Two-way (factorial) between subjects ANCOVA # of IVs and DVs

A

IVs - 1, between subjects, 2 or more levels
DVs - 1, interval characteristics
Covariates - 1 or more

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

Two-way (factorial) repeated-measures ANCOVA

A

assess influence of 1 IV (within groups) on 1 DV after effects of covariates have been removed

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

Two-way (factorial) repeated-measures ANCOVA # of IVs and DVs

Study These Flashcards
A

IVs - 1, within subjects, 2 or more levels
DVs - 1, interval characteristics
Covariates - 1 or more

24
Q

One-way between subjects MANOVA

Study These Flashcards
A

relationship between 1 IV and 2+ DVs

25
One-way between subjects MANOVA # of IVs and DVs
IVs - 1, between subjects, 2+ levels | DVs - 2+, interval characteristics
26
One-way repeated measures MANOVA
relationship between 1 IV (within subjects) and 2+ DVs
27
One-way repeated measures MANOVA # of IVs and DVs
IVs - 1, within subjects, 2+ levels | DVs - 2+, interval characteristics
28
Two-way (factorial) between subjects MANOVA
relationship between 2+ IVs and 2+ DVs
29
Two-way (factorial) between subjects # of IVs and DVs
IVs - 2+, between subjects, 2+ levels | DVs - 2+, interval characteristics
30
Two-way (factorial) repeated measures MANOVA
relationship between 2+ IVs (within subjects) and 2+ DVs
31
Two-way (factorial) repeated-measures MANOVA
IVs - 2+, within subjects, 2+ levels | DVs - 2+, interval characteristics
32
One-way between subjects MANCOVA
relationship between 1 IV and 2 DVs after adjusting for covariates
33
One-way between subjects MANCOVA # of IVs and DVs
IVs - 1, between subjects, 2 or more levels DVs - 2, interval characteristics Covariates - 1+
34
One-way repeated measures MANCOVA
relationship between 1 IV (within subjects) and 2 DVs after adjusting for covariates
35
One-way repeated measures MANCOVA # of IVs and DVs
IVs - 1, within subjects, 2 or more levels DVs - 2, interval characteristics Covariates - 1+
36
Two-way (factorial) between subjects MANCOVA
relationship between IVs and DVs after adjusting for covariates
37
Two-way (factorial) between subjects MANCOVA # of IVs and DVs
IVs - 2+, between subjects, 2+ levels DVs - 2, interval characteristics Covariates - 1+
38
Two-way (factorial) repeated measures MANCOVA
assessing influence of IVs (within subjects) on DVs after adjusting for covariates
39
Two-way (factorial) repeated measures MANCOVA # of IVs and DVs
IVs - 2+, within subjects, 2+ levels DVs - 2, interval characteristics Covariates - 1+
40
Standard Multiple Regression
assesses relationship between IVs and DVs though IVs can be continuous all IVs entered at once but each assessed as it if had been entered last each IV evaluated in terms of what it adds to the prediction of the DV
41
Standard Multiple Regression # of IVs and DVs
IVs - 2+, continuous or discrete | DVs - 1, continuous
42
Sequential (hierarchical) Multiple Regression
Assesses relationship between IVs and DVs though IVs can be continuous IVs entered in an order specified by the researcher order assigned according to logical or theoretical considerations (based on hypothesis or past research) each IV assessed in terms of what it adds to the equation at its own point of entry
43
Sequential (hierarchical) Multiple Regression # of IVs and DVs
IVs - 2+, continuous or discrete | DVs - 1, continuous
44
Path Analysis
extension of Multiple Regression test models of causal relationships among variables, specify and test models of causal relationships among variables estimate direct and indirect effects
45
Goals of Path Analysis
understand patterns of correlations among the regions and explain as much of the regional variable as possible with the model specified focus is on the entire model (reject, modify, or accept)
46
Endogenous Variables
In path analysis those variables modeled as dependent on other variables all arrows point away
47
Exogenous Variables
In path analysis those not dependent on other variables arrows point to it
48
Structural Equation Modeling
per Ullman, 2001: | described as a combination of exploratory factor analysis and multiple regression
49
Manifest Variables
In SEM - serve as indicators of the underlying construct represented by the observable variables
50
Latent Variables
usually theoretical constructs that cannot be observed directly
51
Discriminant Function Analysis
describes major differences among groups following a MANOVA analysis Predict/classify subjects into groups based on a combination of measures Examines the capacity of multiple variables to distinguish groups
52
Factor Analysis
used to identify underlying factors responsible for covariation among independent varables
53
Steps in factor analysis
choice of variables selection of the proper number of factors to retain method of rotation
54
What is the citation for research designs?
Mertler and Vaneeta, 2013
55
What is involved in a two-way mixed model ANOVA?
At least 1 within and 1 between subjects with an IV 2 or more IV's 1 DV
56
What is the purpose of the mixed model ANOVA?
Used to test for differences between two or more independent groups whilst subjecting participants to repeated measures.

Research Comps (3 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2025 Bold Learning Solutions. Terms and Conditions