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