1
Q
What branch of statistics analyzes multiple variables within one model?
A
Multivariate statistics
2
Q
What type of statistics analyzes a single dependent variable?
A
Univariate statistics
3
Q
What statistical approach examines relationships between two variables?
A
Bivariate statistics
4
Q
What term is commonly used for independent variables in multivariate research?
A
Predictors
5
Q
What term is commonly used for dependent variables in multivariate research?
A
Criteria
6
Q
What alternative IV–DV terminology avoids causal implication?
A
Predictor–criterion
7
Q
What type of error is a false positive that increases when multiple univariate tests are performed?
A
Type I error
8
Q
What statistical problem occurs when related outcomes are tested separately, causing the same information to be analyzed more than once?
A
Redundant variance
9
Q
What type of statistical method avoids inflating error rates by testing several dependent variables simultaneously instead of separately?
A
Multivariate tests
10
Q
What research design involves manipulation of independent variables?
A
Experimental research
11
Q
What research design involves measured but not manipulated variables?
A
Nonexperimental research
12
Q
What type of inference is strongest in experimental research?
A
Causal inference
13
Q
What type of inference is limited in nonexperimental research?
A
Causal inference
14
Q
What type of statistics is better suited for survey research with many interrelated measures?
A
Multivariate statistics
15
Q
What type of variable is measured on a smooth scale with meaningful differences?
A
Continuous variable
16
Q
What type of variable consists of a finite set of categories without smooth transitions?
A
Discrete variable
17
Q
What type of variable has exactly two categories?
A
Dichotomous variable
18
Q
What recoding method converts categorical variables into multiple two-level variables?
A
Dummy coding
19
Q
In nonexperimental research, what group is the sample intended to represent?
A
Population
20
Q
In experimental research, what ensures all groups come from the same population before treatment?
A
Random assignment
21
Q
What type of statistics summarizes sample characteristics?
A
Descriptive statistics
22
Q
What type of statistics tests hypotheses about populations?
A
Inferential statistics
23
Q
What term describes variables with zero correlation and no shared variance?
A
Orthogonality
24
Q
What type of variance is shared between correlated variables?
A
Overlapping variance
25
In standard multivariate analysis, what happens to shared variance among predictors?
Unassigned variance
26
What type of variance is credited to each predictor in standard analysis?
Unique variance
27
In sequential analysis, which variable receives shared variance?
First predictor
28
What analytic approach assigns shared variance based on entry order?
Sequential analysis
29
What analytic approach avoids assigning shared variance to any single predictor?
Standard analysis
30
What is a weighted sum of multiple variables used in multivariate analysis called?
Linear combination
31
What term describes a variable created by combining several measured variables?
Supervariable
32
In multivariate analysis, what determines how much each variable contributes to a linear combination?
Weights
33
What statistical problem occurs when too many variables are included relative to sample size?
Overfitting
34
What happens to statistical power as unnecessary variables are added?
Power loss
35
What term describes how likely a statistical test is to find a true effect rather than miss it?
Statistical power
36
What type of error, defined as failing to detect a real effect that truly exists, is reduced by increasing statistical power?
Type II error
37
What structure organizes participants as rows and variables as columns?
Data matrix
38
What matrix summarizes relationships among variables without units?
Correlation matrix
39
What value always appears on the diagonal of a correlation matrix?
One
40
What statistical property does a correlation matrix emphasize?
Relationship strength
41
What matrix preserves original score units and variability?
Covariance matrix
42
What appears on the diagonal of a covariance matrix?
Variance
43
What do off-diagonal values in a covariance matrix represent?
Shared variability
44
What matrix summarizes total variability and joint variability derived from raw data?
S matrix
45
What does the diagonal of the S matrix represent?
Sum of squares
46
What does the off-diagonal of the S matrix represent?
Cross-products
47
What does the sum of squares measure for a single variable?
Total variability
48
What do cross-products measure between two variables?
Joint variability
49
What statistic represents the average spread of scores for a variable?
Variance
50
What operation converts sum of squares into variance?
Averaging
51
What value is used to average the sum of squares in variance calculation?
N minus one
52
What statistic represents the average joint variation between two variables?
Covariance
53
What operation converts cross-products into covariance?
Averaging
54
What does covariance preserve that correlation does not?
Scale units
55
What matrix is obtained by averaging the S matrix values?
Covariance matrix
56
What matrix standardizes covariance to remove scale effects?
Correlation matrix
57
Which bivariate technique treats both variables symmetrically with no outcome implied?
Correlation
58
Which bivariate technique treats one variable as an outcome and the other as a predictor without implying causation?
Regression
59
What does bivariate correlation quantify between two continuous variables?
Association strength
60
What does bivariate regression functionally provide that correlation does not?
Prediction equation
61
Why is bivariate regression not considered a causal analysis?
Nonexperimental design
62
Why are bivariate techniques considered foundational but not multivariate?
Two variables
63
What problem does multiple regression solve compared to bivariate regression?
Multiple predictors
64
In multiple regression, what is being predicted?
Single Dependent Variable
65
What does multiple correlation quantify rather than predict?
Composite association
66
In assessment research, modeling reading achievement from several cognitive domains uses what technique?
Multiple regression
67
Why are correlated predictors acceptable in multiple regression?
Shared variance
68
What type of regression explicitly tests whether later predictors explain variance beyond earlier predictors?
Sequential regression
69
What does sequential regression not establish despite ordered entry?
Causation
70
What multivariate technique assesses the relationship between two sets of continuous variables?
Canonical correlation
71
In cognitive–achievement research, relating cognitive domain profiles to academic profiles uses what method?
Canonical correlation
72
What is the unit of interpretation in canonical correlation, individual variables or variable sets?
Variable sets
73
What type of analysis examines relationships among categorical variables with no designated outcome?
Multiway frequency
74
Why is multiway frequency analysis not framed around IVs and DVs?
Symmetric roles
75
When a categorical outcome is introduced into frequency analysis, what modeling framework is used?
Logit analysis
76
What analytic approach accounts for nesting such as students within schools or repeated measures within individuals?
Multilevel modeling
77
Why does pooling nested data inflate statistical certainty?
Correlated errors
78
In assessment datasets with multiple measures per child, what structural issue must be considered?
Nesting
79
What univariate technique tests group differences on a single outcome variable?
ANOVA
80
What technique tests group differences after adjusting for related continuous variables?
ANCOVA
81
What role do covariates serve in ANCOVA?
Error reduction
82
Why can ANCOVA be conceptually problematic in nonrandomized group designs?
Confounding adjustment
83
What does ANCOVA adjust statistically but not theoretically?
Group differences
84
What analytic family tests the effects of multiple grouping variables simultaneously?
Factorial ANOVA
85
What effect examines whether group differences depend on another grouping variable?
Interaction effect
86
When covariates are added to factorial ANOVA, what is the resulting technique?
Factorial ANCOVA
87
Why is running multiple univariate tests on correlated outcomes problematic?
Type I error
88
What multivariate test evaluates group differences on multiple outcomes simultaneously for two groups?
Hotelling’s T²
89
What multivariate extension allows more than two groups?
MANOVA
90
In MANOVA, what multivariate summary of outcomes is compared across groups?
Centroids
91
Why is MANOVA conducted before examining individual outcome differences?
Omnibus control
92
What technique assesses group differences on multiple outcomes after adjusting for covariates?
MANCOVA
93
In assessment research, adjusting cognitive profiles for age before group comparison uses what method?
MANCOVA
94
What analysis extends MANOVA to designs with more than one independent variable and multiple dependent variables?
Factorial MANOVA
95
What type of research question does factorial MANOVA address compared to one-way MANOVA?
Multiple IV effects
96
In factorial MANOVA, what multivariate quantity is tested rather than individual outcome means?
Centroids
97
What effect tests whether the influence of one independent variable depends on another in factorial MANOVA?
Interaction effect
98
When one independent variable is between-subjects and another is within-subjects in a multivariate design, what analysis is used?
Mixed MANOVA
99
Why can factorial MANOVA examine trends across time or levels of a within-subjects variable?
Repeated measures
100
What extension of factorial MANOVA adjusts the dependent variables for covariates?
Factorial MANCOVA
101
In factorial MANCOVA, what are group differences evaluated on after adjustment?
Adjusted centroids
102
What special form of MANOVA is used when all dependent variables are measured on the same scale?
Profile analysis
103
In profile analysis, what does a grouping variable represent conceptually?
Profile comparison
104
What effect in profile analysis tests whether profiles differ in overall level across groups?
Level effect
105
What effect in profile analysis tests whether the shape of profiles differs across groups?
Shape effect
106
What effect in profile analysis tests whether different variables differ overall regardless of group?
Flatness effect
107
What multivariate approach avoids restrictive assumptions of repeated-measures ANOVA?
Multivariate approach
108
When both multiple dependent variables and repeated measures are present, what is the design sometimes called?
Doubly multivariate
109
What type of research question focuses on predicting which group a case belongs to?
Classification
110
In prediction of group membership, what variable serves as the outcome?
Group membership
111
What analysis predicts group membership from continuous predictors when assumptions are reasonably met?
Discriminant analysis
112
How does discriminant analysis conceptually relate to MANOVA?
Inverse question
113
What does discriminant analysis evaluate beyond statistical significance?
Classification accuracy
114
What aspect of predictors can be examined to see which variables separate groups most strongly?
Discriminant contribution
115
What analysis evaluates predictors of group membership in a theory-driven order?
Sequential discriminant
116
In sequential discriminant analysis, what role do earlier predictors play for later predictors?
Covariates
117
What concept describes evaluating whether predictors add classification power beyond earlier predictors?
Incremental prediction
118
What prediction method is used when all predictors are categorical?
Logit analysis
119
What prediction method allows a mix of continuous and categorical predictors?
Logistic regression
120
What quantity does logistic regression estimate rather than a mean outcome?
Probability
121
What scale is group membership represented on in logistic regression?
Odds
122
What method tests whether predictors add to group classification after adjusting for earlier predictors?
Sequential logistic
123
In sequential logistic regression, what is statistically controlled at each step?
Prior predictors
124
What analysis attempts to predict group membership formed by combinations of attributes?
Factorial discriminant
125
Why is factorial discriminant analysis often discouraged in practice?
Model limitations
126
What alternative framework is usually recommended instead of factorial discriminant analysis?
Factorial MANOVA
127
What type of research question asks about the latent structure underlying variables?
Structure question
128
What analysis empirically summarizes correlations among variables without theoretical assumptions?
Principal components
129
What does principal components analysis aim to reduce?
Dimensionality
130
Does principal components analysis describe structure or explain causes?
Description
131
What analysis is used when there is a theory about underlying latent constructs?
Factor analysis
132
What are the unobserved variables inferred in factor analysis called?
Factors
133
What distinguishes factor analysis from principal components analysis conceptually?
Latent structure
134
What modeling framework combines factor analysis, regression, and canonical correlation?
Structural equation modeling
135
In SEM, what types of variables can be included?
Latent variables
136
What aspect of SEM evaluates how well a hypothesized model matches observed data?
Model fit
137
What type of research question focuses on when events occur?
Time course
138
What analysis examines how long it takes for an event to occur?
Survival analysis
139
In survival analysis, what serves as the dependent variable?
Time
140
What analysis examines change in a variable across many time points?
Time-series analysis
141
What role does time play in time-series analysis?
Primary IV
142
When only two variables are involved in assessing a relationship, which statistic is appropriate?
Bivariate r
143
When one outcome is related to several predictors, which statistic is appropriate?
Multiple R
144
What technique examines relationships between multiple predictors and multiple outcomes simultaneously?
Canonical correlation
145
What type of variables are most relationship techniques in Section 2.2 designed for?
Continuous variables
146
When all variables are discrete, what analytic family is preferred?
Multiway frequency
147
What analysis is used for group differences when there is only one dependent variable?
ANOVA
148
What analysis is used for group differences when there are multiple dependent variables?
MANOVA
149
Conceptually, what does MANOVA do before testing group differences?
DV combination
150
What univariate technique does MANOVA conceptually extend?
ANOVA
151
What assumption of repeated-measures ANOVA is often violated?
Sphericity
152
What multivariate approach avoids the sphericity assumption by combining different dependent variables?
MANOVA
153
What multivariate approach avoids sphericity by combining repeated measurements of the same dependent variable?
Profile analysis
154
What design combines between- and within-subjects factors using a multivariate framework?
Mixed MANOVA
155
When both repeated measures and multiple dependent variables are present, what design is used?
Doubly multivariate
156
Why are multivariate extensions often less powerful than univariate tests when assumptions are met?
Power tradeoff
157
What type of dependent variable is used in both discriminant analysis and logistic regression?
Discrete DV
158
In discriminant analysis, what type of predictors are typically used?
Continuous predictors
159
What complication arises in discriminant analysis when there are more than two groups?
Multiple functions
160
In discriminant analysis, who determines how groups are best separated?
Analysis
161
What type of predictors can logistic regression accommodate?
Mixed predictors
162
What does logistic regression predict instead of group membership directly?
Probability
163
What familiar univariate technique does logistic regression conceptually resemble?
Chi-square
164
What transformation distinguishes logistic regression from linear regression?
Exponential link
165
What type of research question focuses on how variables group together?
Structure question
166
What two techniques are most closely aligned for studying structure?
PCA, FA
167
Multivariate Statistics
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