Unit 12: Multivariate Analysis - Practice Quiz

DEMGN832 — Research Methodology 60 Questions
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1 What is the main purpose of classification in multivariate analysis?

Classification Easy
A. To calculate averages for each variable
B. To assign cases to predefined groups
C. To remove variables from a dataset
D. To arrange observations by date

2 Which type of data is normally required to train a supervised classification model?

Classification Easy
A. Data containing one observation
B. Data containing no variables
C. Data with known class labels
D. Data with missing class labels

3 In a classification problem, the dependent variable is usually:

Classification Easy
A. A correlation coefficient
B. A random error term
C. A categorical variable
D. A continuous ratio

4 What is the basic objective of factor analysis?

Important methods of factor analysis Easy
A. To rank individual observations
B. To forecast a time series
C. To compare group percentages
D. To identify underlying factors

5 Principal component analysis primarily explains which type of variance?

Important methods of factor analysis Easy
A. Total variance
B. Error variance only
C. Between-group variance only
D. Common variance only

6 Principal axis factoring mainly focuses on:

Important methods of factor analysis Easy
A. Mean differences among groups
B. Common variance among variables
C. Total variance among variables
D. Distances among cluster centers

7 Which factor extraction method estimates parameters by maximizing a likelihood function?

Important methods of factor analysis Easy
A. Ward's method
B. Maximum likelihood
C. Varimax rotation
D. Multidimensional scaling

8 Which matrix is commonly examined at the beginning of factor analysis?

Factor analysis procedure Easy
A. Correlation matrix
B. Payoff matrix
C. Distance matrix
D. Confusion matrix

9 What does the Kaiser-Meyer-Olkin (KMO) measure assess?

Factor analysis procedure Easy
A. Classification accuracy
B. Sampling adequacy
C. Cluster separation
D. Preference strength

10 According to the Kaiser criterion, which factors are generally retained?

Factor analysis procedure Easy
A. Factors with eigenvalues above
B. Factors with eigenvalues below
C. Factors with loadings equal to
D. Factors with communalities below

11 Why is factor rotation performed?

Rotation in factor analysis Easy
A. To create new observations
B. To increase the sample size
C. To improve factor interpretability
D. To remove all correlations

12 Which of the following is an orthogonal rotation method?

Rotation in factor analysis Easy
A. Varimax
B. Oblimin
C. Quartimin
D. Promax

13 What does an oblique rotation allow?

Rotation in factor analysis Easy
A. Factors to be correlated
B. Observations to form clusters
C. Factors to remain identical
D. Variables to become categorical

14 What is the main objective of cluster analysis?

Overview of cluster analysis Easy
A. To estimate factor loadings
B. To group similar observations
C. To predict a labeled category
D. To measure consumer utility

15 Which diagram commonly displays the results of hierarchical clustering?

Overview of cluster analysis Easy
A. Scatter matrix
B. Perceptual map
C. Scree plot
D. Dendrogram

16 What must usually be specified before applying the -means clustering method?

Overview of cluster analysis Easy
A. The utility scores
B. The class labels
C. The number of clusters
D. The number of factors

17 What is discriminant analysis mainly used to predict?

Discriminant analysis Easy
A. Membership in unknown clusters
B. Positions on a perceptual map
C. Membership in predefined groups
D. Utilities of product attributes

18 A discriminant function is usually formed as:

Discriminant analysis Easy
A. A matrix of preference ranks
B. A graph of factor eigenvalues
C. A list of cluster labels
D. A linear combination of predictors

19 What does multidimensional scaling commonly produce?

Multidimensional scaling Easy
A. A hierarchy of clusters
B. A spatial map of objects
C. A list of class predictions
D. A table of factor loadings

20 What is conjoint analysis primarily used to study?

Conjoint analysis Easy
A. Preferences for product attributes
B. Correlations among latent factors
C. Distances between cluster centers
D. Differences between class labels

21 A researcher wants to predict customer loyalty from satisfaction, perceived value, and service quality. How should this multivariate problem be classified?

Classification Medium
A. An interdependence technique with no criterion variable
B. An interdependence technique based only on distances
C. A dependence technique with several criterion variables
D. A dependence technique with one criterion variable

22 A study examines 15 attitude variables without specifying any variable as an outcome and seeks a smaller set of underlying dimensions. Which classification is most appropriate?

Classification Medium
A. A dependence method for prediction
B. An interdependence method for case classification
C. A dependence method for group comparison
D. An interdependence method for data reduction

23 A researcher wants to summarize the total variance in 12 observed variables into a few weighted composites. Which method is most suitable?

Important methods of factor analysis Medium
A. Principal axis factoring
B. Canonical discriminant analysis
C. Maximum likelihood factoring
D. Principal component analysis

24 A researcher is interested in latent constructs that explain only the shared variance among measured variables. Which method best matches this objective?

Important methods of factor analysis Medium
A. Hierarchical cluster analysis
B. Principal axis factoring
C. Multidimensional scaling
D. Principal component analysis

25 A researcher wants to test the statistical fit of a factor model and construct confidence intervals, assuming approximate multivariate normality. Which extraction method is most appropriate?

Important methods of factor analysis Medium
A. Maximum likelihood extraction
B. Principal component extraction
C. Centroid factor extraction
D. Unweighted least-squares extraction

26 A dataset produces a Kaiser-Meyer-Olkin value of and a significant Bartlett's test with . What is the best conclusion?

Factor analysis procedure Medium
A. The factors require an oblique rotation
B. The variables have perfect multicollinearity
C. The data are suitable for factor analysis
D. The sample must be divided into clusters

27 After extraction, one variable has a communality of , while all other variables have communalities above . What does the value indicate?

Factor analysis procedure Medium
A. The retained factors explain little variance in that variable
B. The retained factors explain of that variable's variance
C. The variable has a loading of on every factor
D. The variable explains little variance in the retained factors

28 The first six eigenvalues from a correlation matrix are , , , , , and . Under the Kaiser criterion, how many factors should initially be retained?

Factor analysis procedure Medium
A. Three factors
B. Six factors
C. Four factors
D. Two factors

29 A theory states that anxiety and depression are related latent constructs. Which rotation is most appropriate when extracting these factors?

Rotation in factor analysis Medium
A. Quartimax rotation
B. Oblimin rotation
C. Varimax rotation
D. Equamax rotation

30 After varimax rotation, a variable has loadings of , , and on three factors. How should the variable usually be interpreted?

Rotation in factor analysis Medium
A. It represents all three factors equally
B. It primarily represents the first factor
C. It primarily represents the second factor
D. It primarily represents the third factor

31 A retailer knows in advance that customers must be divided into four market segments and has a large numerical dataset. Which method is most appropriate?

Overview of cluster analysis Medium
A. Discriminant analysis with four predictors
B. Factor analysis with four factors
C. K-means clustering with
D. Single-linkage clustering with four cases

32 Income is measured in dollars and age is measured in years. Before clustering customers using Euclidean distance, what should the researcher generally do?

Overview of cluster analysis Medium
A. Convert both variables to ranks
B. Reverse-score the variables
C. Remove the variable with less variance
D. Standardize the variables

33 A researcher uses single-linkage hierarchical clustering and obtains a long sequence of cases joined through close neighbors. Which known tendency does this illustrate?

Overview of cluster analysis Medium
A. The rotation effect
B. The chaining effect
C. The suppression effect
D. The scaling effect

34 A bank has historical data in which applicants are already labeled as low, medium, or high credit risk. It wants to classify new applicants using financial ratios. Which technique is appropriate?

Discriminant analysis Medium
A. Hierarchical cluster analysis
B. Exploratory factor analysis
C. Multiple discriminant analysis
D. Metric multidimensional scaling

35 A discriminant function for two groups is . If an observation has and , what is its discriminant score?

Discriminant analysis Medium
A.
B.
C.
D.

36 Box's M test is significant in a discriminant analysis involving several groups. Which assumption is most directly questioned?

Discriminant analysis Medium
A. Independence of group memberships
B. Equality of covariance matrices
C. Equality of group sample sizes
D. Linearity of factor loadings

37 Consumers rate the pairwise dissimilarity of six smartphone brands. A researcher wants a two-dimensional map in which similar brands appear close together. Which technique should be used?

Multidimensional scaling Medium
A. Principal axis factoring
B. Multidimensional scaling
C. Two-stage cluster sampling
D. Multiple discriminant analysis

38 A two-dimensional multidimensional scaling solution has Stress , while a one-dimensional solution has Stress . What is the most reasonable interpretation?

Multidimensional scaling Medium
A. Both solutions reproduce the distances equally well
B. The one-dimensional solution reproduces the distances better
C. The two-dimensional solution reproduces the distances better
D. Stress cannot be used to compare these solutions

39 In a conjoint study of laptops, a respondent's part-worths are for a low price, for a high-resolution screen, and for a light weight. Ignoring the intercept, what is the total utility of a laptop with all three features?

Conjoint analysis Medium
A.
B.
C.
D.

40 In a conjoint analysis, the utility range for price is , for brand is , and for warranty is . What is the relative importance of price?

Conjoint analysis Medium
A.
B.
C.
D.

41 A researcher has 12 continuous variables and wants to assign observations to one of four groups. The group labels are known for a training sample, but the group covariance matrices may differ. Which classification is most appropriate?

Classification Hard
A. Supervised classification using quadratic discriminant analysis
B. Unsupervised classification using Ward's clustering
C. Unsupervised classification using principal component analysis
D. Supervised classification using linear discriminant analysis

42 A binary classifier estimates . A false negative costs 8 units, a false positive costs 2 units, and correct decisions have zero cost. Under minimum expected loss, how should the observation be classified?

Classification Hard
A. Classify as 1 because
B. Classify as 0 because
C. Classify as 0 because
D. Classify as 1 because

43 Which statement correctly distinguishes principal component analysis from principal axis factoring when both are applied to the same correlation matrix?

Important methods of factor analysis Hard
A. PCA models only common variance, while principal axis factoring models total observed variance
B. PCA requires multivariate normality, while principal axis factoring always requires interval data
C. PCA initially uses unit diagonal entries, while principal axis factoring uses communality estimates
D. PCA estimates unique variances, while principal axis factoring fixes all unique variances at zero

44 A dataset contains strongly non-normal indicators, and the researcher wants latent common factors without relying on a multivariate-normal likelihood-ratio test. Which extraction method is most defensible?

Important methods of factor analysis Hard
A. Unweighted least squares PCA
B. Canonical discriminant factoring
C. Principal axis factoring
D. Maximum likelihood factoring

45 Under maximum likelihood factor analysis, which result can be formally evaluated when its assumptions are sufficiently satisfied?

Important methods of factor analysis Hard
A. Whether the observed variables form mutually exclusive classification groups
B. Whether every retained factor explains more variance than every observed variable
C. Whether rotated factor scores are uniquely determined for every observation
D. Whether a specified number of common factors adequately fits the covariance matrix

46 For three standardized variables, the inverse correlation matrix is

Using , what additional operation is required before computing the KMO values?

Factor analysis procedure Hard
A. Rotate the inverse matrix using an orthogonal criterion
B. Replace inverse-matrix diagonals with estimated communalities
C. Standardize each inverse-matrix row to unit variance
D. Convert inverse-matrix off-diagonals into partial correlations

47 A sample correlation matrix has eigenvalues . The corresponding mean eigenvalues from parallel random datasets are . How many factors should parallel analysis retain?

Factor analysis procedure Hard
A. Three factors
B. Four factors
C. One factor
D. Two factors

48 After extracting a two-factor model, one variable has loadings and . Assuming standardized variables and no additional factor contributions, what are its communality and uniqueness?

Factor analysis procedure Hard
A. Communality and uniqueness
B. Communality and uniqueness
C. Communality and uniqueness
D. Communality and uniqueness

49 An unrotated orthogonal loading matrix is transformed as , where . Which quantity is necessarily unchanged for every observed variable?

Rotation in factor analysis Hard
A. Its loading on the first retained factor
B. Its ranking by the largest absolute loading
C. Its communality across the retained factors
D. Its correlation with each individual factor

50 In an oblique factor solution, variable has pattern coefficients , and the factor correlation matrix is . What is the structure coefficient of with the second factor?

Rotation in factor analysis Hard
A.
B.
C.
D.

51 A researcher expects two substantive constructs to be correlated but applies varimax rotation. What is the most important interpretive risk?

Rotation in factor analysis Hard
A. The resulting factors will no longer reproduce the correlation matrix
B. The rotation will necessarily change every variable's communality
C. The extraction will necessarily retain too many common factors
D. The solution may redistribute shared construct variance into cross-loadings

52 A cluster analysis uses Euclidean distance on income measured in dollars and satisfaction measured on a seven-point scale. Income has far greater numerical variance. What is the most defensible preprocessing decision?

Overview of cluster analysis Hard
A. Retain raw scales because clustering automatically adjusts variable variance
B. Convert Euclidean distances into squared correlations after clustering
C. Standardize observations within each cluster after estimating memberships
D. Standardize variables using substantively justified scales before clustering

53 Under Ward's method with squared Euclidean distance, clusters and contain 4 and 6 cases, and their centroids are 5 units apart. What is the increase in within-cluster sum of squares if they are merged?

Overview of cluster analysis Hard
A.
B.
C.
D.

54 A hierarchical single-linkage solution joins two dense, well-separated groups through a sequence of sparse intermediate observations. Which diagnosis best explains the result?

Overview of cluster analysis Hard
A. A rotation effect caused by correlated cluster axes
B. A centroid reversal caused by unequal cluster sizes
C. A suppression effect caused by negative communalities
D. A chaining effect caused by nearest-neighbor links

55 Two groups have multivariate normal distributions with equal covariance matrices but unequal prior probabilities. Relative to equal priors, how does incorporating the unequal priors affect the linear discriminant boundary?

Discriminant analysis Hard
A. It converts the linear boundary into a quadratic boundary
B. It changes the orientation while retaining the same boundary intercept
C. It shifts the intercept while retaining the same boundary orientation
D. It leaves both the orientation and intercept unchanged

56 In a three-group discriminant analysis with five predictors, what is the maximum number of nonzero canonical discriminant functions?

Discriminant analysis Hard
A. Four functions
B. Three functions
C. Two functions
D. Five functions

57 A study applies quadratic discriminant analysis with 80 predictors but only 25 observations in each group. What is the central estimation problem?

Discriminant analysis Hard
A. The pooled covariance matrix must equal the identity matrix
B. Each group covariance matrix is singular or highly unstable
C. The discriminant functions cannot include group prior probabilities
D. The group means become identical after predictor standardization

58 A nonmetric multidimensional scaling solution has low stress, but its recovered distances are not linearly related to the original dissimilarities. Why can the solution still be valid?

Multidimensional scaling Hard
A. Nonmetric MDS primarily preserves the rank order of dissimilarities
B. Nonmetric MDS primarily preserves the covariance of object coordinates
C. Nonmetric MDS constrains every disparity to equal its original value
D. Nonmetric MDS requires only equal average distances among all objects

59 In classical MDS, double-centering the squared dissimilarity matrix produces a matrix with several substantial negative eigenvalues. What is the best interpretation?

Multidimensional scaling Hard
A. The dissimilarities are not exactly representable in Euclidean space
B. The configuration is Euclidean but requires only one dimension
C. The original dissimilarities must have been measured on a ratio scale
D. The object coordinates are unique up to translation but not rotation

60 An effects-coded conjoint model estimates level utilities for a three-level attribute as for level 1 and for level 2. What utility is implied for level 3?

Conjoint analysis Hard
A.
B.
C.
D.