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