Test your knowledge.Receive immediate feedback.You find all answers in the book. Quiz | Factor Analysis /24 59 Quiz | Factor Analysis 1 / 24 What is one of the main objectives of factor analysis? To reduce a large number of correlating variables to a fewer number of factors To increase the variance-covariance matrix To increase the number of correlating variables To decrease the number of factors 2 / 24 What is the primary assumption about highly correlated variables in factor analysis? They have no correlation. They should be reduced to a single variable. They are the result of common causes (factors). They are not suitable for analysis. 3 / 24 What does a high correlation between two variables indicate in factor analysis? They should be eliminated from the analysis. They can be combined into a common factor. They are weakly correlated with other variables. They are unsuitable for factor analysis. 4 / 24 Explain why the variable "I have difficulty in imagining Calvé in my mind” has a negative factor loading for factor 1. The item is a reverse coded item, and has, thus, a negative factor loading. This must be a mistake. Factor loadings need to be positive. 5 / 24 In the context of factor scores, what does a factor score of 0 signify? An object has the highest rating on the factor. An object is rated above average on the factor. An object is rated below average on the factor. An object has an average rating on the factor. 6 / 24 What is the difference between orthogonal and oblique rotation methods? Oblique rotation methods assume uncorrelated factors, while orthogonal methods allow for correlation between factors. Orthogonal rotation methods assume uncorrelated factors, while oblique methods allow for correlation between factors. There is no difference. 7 / 24 What is the difference between communality and eigenvalue? Check 8 / 24 What does the communality of a variable in factor analysis measure? The eigenvalue of the variable The proportion of variance in the variable explained by the factors The sum of the squared factor loadings for the variable The uniqueness of the variable 9 / 24 What is the first step in conducting a factor analysis? Determining the factor scores Evaluating the suitability of the data Extracting the factors Interpreting the factors 10 / 24 What does the fundamental theorem of factor analysis state? It explains how to standardize data. It calculates the variance of factors It defines the correlation matrix. It relates observed data to unobserved factors. 11 / 24 In factor analysis, what do factor loadings (ajq) represent? The correlation between an observed variable and the extracted factor The sum of the squared factor loadings The variance of the observed variables The number of observations (cases) 12 / 24 When is a correlation matrix considered suitable for factor analysis according to the Bartlett test of sphericity? When the variables in the sample are uncorrelated When the correlation matrix is equal to the inversed covariance matrix When the degrees of freedom are low When the correlation matrix is not an identity matrix 13 / 24 In what step of factor analysis is the user required to decide how many factors are to be extracted? Step 3: Interpreting the factors Step 2: Extracting the factors Step 1: Checking data suitability Step 4: Assessing factor scores 14 / 24 What does CFA refer to when it mentions "reflective measurement models"? Models that reflect hypothetical constructs via measurement variables. Models that reflect the data structure without assumptions. Models that involve exploratory data analysis. Models that are highly complex and difficult to interpret. 15 / 24 What is the H0 of the Bartlett test of sphericity? The variables in the population are uncorrelated. The variables in the sample are correlated. The variables in the sample are uncorrelated. The variables in the population are correlated. 16 / 24 In factor analysis, what does the procedure primarily analyze? The mean of the data The regression coefficients The correlation matrix The covariance matrix 17 / 24 What statement(s) related to the KMO and MSA criterion are correct? MSA assesses the suitability of a single variable. There is no difference between the two criteria. Both criteria measure the same. KMO assesses the suitability of the correlation matrix. 18 / 24 What does a negative factor score represent in factor analysis? An object has an average rating on the factor. An object is rated below average on the factor. An object is rated above average on the factor. An object has the highest rating on the factor. 19 / 24 What is the primary objective of factor analysis compared to principal component analysis (PCA)? To eliminate unique variance in observed variables To reduce the dimensionality of data To uncover the common causes (factors) of observed variables and their correlations To maximize the explained variance by the extracted factors 20 / 24 What are factor loadings in factor analysis? The strength of the correlations between original variables and the factors Assessment values per person The factors themselves The number of factors extracted 21 / 24 What is the primary purpose of determining factor scores in factor analysis? To reduce the number of factors To calculate the eigenvalues of factors To determine the factor loadings To understand how objects score on the factors 22 / 24 In a factor analysis, what do the factor scores represent? Number of factors extracted Original variables Values per person on the latent factors Strength of correlations 23 / 24 How are summated scales calculated for factor scores in factor analysis? By using regression analysis on factor loadings By taking the sum of the highest factor loadings for each factor By multiplying factor loadings by the number of variables By calculating the mean of the high-loading variables for each factor 24 / 24 How is the suitability of data for factor analysis typically evaluated? By assessing inter-item reliability By calculating the correlation matrix By examining means and standard deviations By conducting a regression analysis Your score is 0% Restart quiz Learn more…MethodsServiceAbout us ContactFeedbackOrder data etc. GeneralImprintPrivacy notice
