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 conducting a regression analysis By examining means and standard deviations By assessing inter-item reliability By calculating the correlation matrix 2 / 24 What is the first step in conducting a factor analysis? Evaluating the suitability of the data Interpreting the factors Extracting the factors Determining the factor scores 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 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. 5 / 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 reflect the data structure without assumptions. Models that involve exploratory data analysis. 6 / 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 7 / 24 What does a high correlation between two variables indicate in factor analysis? They are weakly correlated with other variables. They are unsuitable for factor analysis. They should be eliminated from the analysis. They can be combined into a common factor. 8 / 24 What does the fundamental theorem of factor analysis state? It explains how to standardize data. It relates observed data to unobserved factors. It calculates the variance of factors It defines the correlation matrix. 9 / 24 In factor analysis, what does the procedure primarily analyze? The correlation matrix The mean of the data The covariance matrix The regression coefficients 10 / 24 What statement(s) related to the KMO and MSA criterion are correct? KMO assesses the suitability of the correlation matrix. MSA assesses the suitability of a single variable. There is no difference between the two criteria. Both criteria measure the same. 11 / 24 In the context of factor scores, what does a factor score of 0 signify? An object is rated above average on the factor. An object has the highest rating on the factor. An object has an average rating on the factor. An object is rated below average on the factor. 12 / 24 What is one of the main objectives of factor analysis? To increase the number of correlating variables To decrease the number of factors To increase the variance-covariance matrix To reduce a large number of correlating variables to a fewer number of factors 13 / 24 What is the difference between communality and eigenvalue? Check 14 / 24 What does the communality of a variable in factor analysis measure? The uniqueness 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 eigenvalue of the variable 15 / 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 16 / 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. 17 / 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 18 / 24 What is the primary purpose of determining factor scores in factor analysis? To calculate the eigenvalues of factors To determine the factor loadings To understand how objects score on the factors To reduce the number of factors 19 / 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 uncover the common causes (factors) of observed variables and their correlations To reduce the dimensionality of data To eliminate unique variance in observed variables 20 / 24 In factor analysis, what do factor loadings (ajq) represent? The number of observations (cases) The correlation between an observed variable and the extracted factor The sum of the squared factor loadings The variance of the observed variables 21 / 24 What does a negative factor score represent in factor analysis? 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. An object has the highest rating on the factor. 22 / 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. 23 / 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 multiplying factor loadings by the number of variables By using regression analysis on factor loadings 24 / 24 What is the H0 of the Bartlett test of sphericity? The variables in the sample are uncorrelated. The variables in the population are correlated. The variables in the sample are correlated. The variables in the population are uncorrelated. Your score is 0% Restart quiz Learn more…MethodsServiceAbout us ContactFeedbackOrder data etc. GeneralImprintPrivacy notice
