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