Test your knowledge.Receive immediate feedback.You find all answers in the book. Quiz | Factor Analysis /24 59 Quiz | Factor Analysis 1 / 24 What does a negative factor score represent in factor analysis? An object has an average rating on the factor. 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. 2 / 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 3 / 24 In factor analysis, what do factor loadings (ajq) represent? The sum of the squared factor loadings The correlation between an observed variable and the extracted factor The number of observations (cases) The variance of the observed variables 4 / 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. 5 / 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 6 / 24 What does a high correlation between two variables indicate in factor analysis? They can be combined into a common factor. They should be eliminated from the analysis. They are weakly correlated with other variables. They are unsuitable for factor analysis. 7 / 24 What is one of the main objectives of factor analysis? To increase the variance-covariance matrix To increase the number of correlating variables To decrease the number of factors To reduce a large number of correlating variables to a fewer number of factors 8 / 24 What is the primary assumption about highly correlated variables in factor analysis? They have no correlation. They are not suitable for analysis. They are the result of common causes (factors). They should be reduced to a single variable. 9 / 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. 10 / 24 What is the difference between communality and eigenvalue? Check 11 / 24 In a factor analysis, what do the factor scores represent? Original variables Strength of correlations Values per person on the latent factors Number of factors extracted 12 / 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 13 / 24 What does the fundamental theorem of factor analysis state? It defines the correlation matrix. It relates observed data to unobserved factors. It explains how to standardize data. It calculates the variance of factors 14 / 24 What is the difference between orthogonal and oblique rotation methods? Orthogonal rotation methods assume uncorrelated factors, while oblique methods allow for correlation between factors. There is no difference. Oblique rotation methods assume uncorrelated factors, while orthogonal methods allow for correlation between factors. 15 / 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 16 / 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 2: Extracting the factors Step 3: Interpreting the factors Step 4: Assessing factor scores 17 / 24 What is the first step in conducting a factor analysis? Interpreting the factors Evaluating the suitability of the data Extracting the factors Determining the factor scores 18 / 24 What is the H0 of the Bartlett test of sphericity? The variables in the population are uncorrelated. The variables in the population are correlated. The variables in the sample are correlated. The variables in the sample are uncorrelated. 19 / 24 How is the suitability of data for factor analysis typically evaluated? By calculating the correlation matrix By assessing inter-item reliability By conducting a regression analysis By examining means and standard deviations 20 / 24 What does CFA refer to when it mentions "reflective measurement models"? Models that involve exploratory data analysis. Models that reflect hypothetical constructs via measurement variables. Models that reflect the data structure without assumptions. Models that are highly complex and difficult to interpret. 21 / 24 What is the primary purpose of determining factor scores in factor analysis? To determine the factor loadings To calculate the eigenvalues of factors To understand how objects score on the factors To reduce the number of factors 22 / 24 What does the communality of a variable in factor analysis measure? The uniqueness of the variable The eigenvalue of the variable The sum of the squared factor loadings for the variable The proportion of variance in the variable explained by the factors 23 / 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 below average on the factor. An object is rated above average on the factor. An object has the highest rating on the factor. 24 / 24 In factor analysis, what does the procedure primarily analyze? The regression coefficients The mean of the data The covariance matrix The correlation matrix Your score is 0% Restart quiz Learn more…MethodsServiceAbout us ContactFeedbackOrder data etc. GeneralImprintPrivacy notice
