Test your knowledge.Receive immediate feedback.You find all answers in the book. Quiz | Factor Analysis /24 59 Quiz | Factor Analysis 1 / 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. 2 / 24 How is the suitability of data for factor analysis typically evaluated? By examining means and standard deviations By calculating the correlation matrix By assessing inter-item reliability By conducting a regression analysis 3 / 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 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 increase the number of correlating variables To reduce a large number of correlating variables to a fewer number of factors 5 / 24 What is the H0 of the Bartlett test of sphericity? The variables in the sample are uncorrelated. The variables in the sample are correlated. The variables in the population are uncorrelated. The variables in the population are correlated. 6 / 24 What is the primary assumption about highly correlated variables in factor analysis? They are the result of common causes (factors). They are not suitable for analysis. They have no correlation. They should be reduced to a single variable. 7 / 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 above average on the factor. An object is rated below average on the factor. An object has an average rating on the factor. 8 / 24 What is the first step in conducting a factor analysis? Interpreting the factors Extracting the factors Determining the factor scores Evaluating the suitability of the data 9 / 24 What does a negative factor score represent in factor analysis? An object is rated above average on the factor. An object has an average rating on the factor. An object is rated below average on the factor. An object has the highest rating on the factor. 10 / 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 not an identity matrix When the correlation matrix is equal to the inversed covariance matrix When the degrees of freedom are low 11 / 24 What are factor loadings in factor analysis? The strength of the correlations between original variables and the factors Assessment values per person The number of factors extracted The factors themselves 12 / 24 How are summated scales calculated for factor scores in factor analysis? By multiplying factor loadings by the number of variables By taking the sum of the highest factor loadings for each factor By using regression analysis on factor loadings By calculating the mean of the high-loading variables for each factor 13 / 24 What is the difference between communality and eigenvalue? Check 14 / 24 In factor analysis, what does the procedure primarily analyze? The correlation matrix The covariance matrix The regression coefficients The mean of the data 15 / 24 What does the communality of a variable in factor analysis measure? The proportion of variance in the variable explained by the factors The eigenvalue of the variable The uniqueness of the variable The sum of the squared factor loadings for the variable 16 / 24 In factor analysis, what do factor loadings (ajq) represent? The sum of the squared factor loadings The variance of the observed variables The correlation between an observed variable and the extracted factor The number of observations (cases) 17 / 24 What does a high correlation between two variables indicate in factor analysis? They can be combined into a common factor. They are unsuitable for factor analysis. They should be eliminated from the analysis. They are weakly correlated with other variables. 18 / 24 In a factor analysis, what do the factor scores represent? Original variables Number of factors extracted Values per person on the latent factors Strength of correlations 19 / 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. 20 / 24 In what step of factor analysis is the user required to decide how many factors are to be extracted? Step 3: Interpreting the factors Step 4: Assessing factor scores Step 2: Extracting the factors Step 1: Checking data suitability 21 / 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. 22 / 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. 23 / 24 What does the fundamental theorem of factor analysis state? It relates observed data to unobserved factors. It defines the correlation matrix. It explains how to standardize data. It calculates the variance of factors 24 / 24 What is the primary objective of factor analysis compared to principal component analysis (PCA)? To reduce the dimensionality of data To eliminate unique variance in observed variables To maximize the explained variance by the extracted factors To uncover the common causes (factors) of observed variables and their correlations Your score is 0% Restart quiz Learn more…MethodsServiceAbout us ContactFeedbackOrder data etc. GeneralImprintPrivacy notice
