Test your knowledge.Receive immediate feedback.You find all answers in the book. Quiz | Factor Analysis /24 59 Quiz | Factor Analysis 1 / 24 How is the suitability of data for factor analysis typically evaluated? By calculating the correlation matrix By assessing inter-item reliability By examining means and standard deviations By conducting a regression analysis 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 not suitable for analysis. They are the result of common causes (factors). 3 / 24 In factor analysis, what does the procedure primarily analyze? The mean of the data The regression coefficients The covariance matrix The correlation matrix 4 / 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. 5 / 24 What is the first step in conducting a factor analysis? Determining the factor scores Interpreting the factors Extracting the factors Evaluating the suitability of the data 6 / 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 7 / 24 How are summated scales calculated for factor scores in factor analysis? 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 using regression analysis on factor loadings By multiplying factor loadings by the number of variables 8 / 24 What does a negative factor score represent in factor analysis? An object has the highest rating on the factor. 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. 9 / 24 What is one of the main objectives of factor analysis? To decrease the number of factors To increase the variance-covariance matrix To increase the number of correlating variables To reduce a large number of correlating variables to a fewer number of factors 10 / 24 In a factor analysis, what do the factor scores represent? Values per person on the latent factors Number of factors extracted Original variables Strength of correlations 11 / 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. 12 / 24 In factor analysis, what do factor loadings (ajq) represent? The variance of the observed variables The sum of the squared factor loadings The number of observations (cases) The correlation between an observed variable and the extracted factor 13 / 24 What are factor loadings in factor analysis? Assessment values per person The factors themselves The number of factors extracted The strength of the correlations between original variables and the factors 14 / 24 What is the difference between communality and eigenvalue? Check 15 / 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 has an average rating on the factor. An object is rated above average on the factor. An object is rated below average on the factor. 16 / 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 variables in the sample are uncorrelated When the degrees of freedom are low When the correlation matrix is not an identity matrix 17 / 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 eliminate unique variance in observed variables To maximize the explained variance by the extracted factors To reduce the dimensionality of data 18 / 24 What is the primary purpose of determining factor scores in factor analysis? To understand how objects score on the factors To determine the factor loadings To calculate the eigenvalues of factors To reduce the number of factors 19 / 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 4: Assessing factor scores Step 2: Extracting the factors 20 / 24 What does a high correlation between two variables indicate in factor analysis? They are unsuitable for factor analysis. They are weakly correlated with other variables. They should be eliminated from the analysis. They can be combined into a common factor. 21 / 24 What is the H0 of the Bartlett test of sphericity? The variables in the population are correlated. The variables in the sample are correlated. The variables in the population are uncorrelated. The variables in the sample are uncorrelated. 22 / 24 What statement(s) related to the KMO and MSA criterion are correct? MSA assesses the suitability of a single variable. KMO assesses the suitability of the correlation matrix. There is no difference between the two criteria. Both criteria measure the same. 23 / 24 What is the difference between orthogonal and oblique rotation methods? There is no difference. Orthogonal rotation methods assume uncorrelated factors, while oblique methods allow for correlation between factors. Oblique rotation methods assume uncorrelated factors, while orthogonal methods allow for correlation between factors. 24 / 24 What does the fundamental theorem of factor analysis state? It relates observed data to unobserved factors. It calculates the variance of factors It explains how to standardize data. It defines the correlation matrix. Your score is 0% Restart quiz Learn more…MethodsServiceAbout us ContactFeedbackOrder data etc. GeneralImprintPrivacy notice
