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 When is a correlation matrix considered suitable for factor analysis according to the Bartlett test of sphericity? When the degrees of freedom are low When the correlation matrix is not an identity matrix When the variables in the sample are uncorrelated When the correlation matrix is equal to the inversed covariance matrix 3 / 24 What is the H0 of the Bartlett test of sphericity? The variables in the sample are correlated. The variables in the population are correlated. The variables in the population are uncorrelated. The variables in the sample are uncorrelated. 4 / 24 What is the primary objective of factor analysis compared to principal component analysis (PCA)? To eliminate unique variance in observed variables To reduce the dimensionality of data To uncover the common causes (factors) of observed variables and their correlations To maximize the explained variance by the extracted factors 5 / 24 How are summated scales calculated for factor scores in factor analysis? 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 By calculating the mean of the high-loading variables for each factor 6 / 24 What is one of the main objectives of factor analysis? To increase the number of correlating variables 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 7 / 24 What is the primary purpose of determining factor scores in factor analysis? To understand how objects score on the factors To reduce the number of factors To determine the factor loadings To calculate the eigenvalues of factors 8 / 24 In a factor analysis, what do the factor scores represent? Original variables Strength of correlations Number of factors extracted Values per person on the latent factors 9 / 24 What is the primary assumption about highly correlated variables in factor analysis? They are not suitable for analysis. They have no correlation. They should be reduced to a single variable. They are the result of common causes (factors). 10 / 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 2: Extracting the factors Step 3: Interpreting the factors Step 1: Checking data suitability 11 / 24 What is the difference between communality and eigenvalue? Check 12 / 24 In factor analysis, what do factor loadings (ajq) represent? The correlation between an observed variable and the extracted factor The sum of the squared factor loadings The number of observations (cases) The variance of the observed variables 13 / 24 What does CFA refer to when it mentions "reflective measurement models"? Models that are highly complex and difficult to interpret. Models that reflect the data structure without assumptions. Models that involve exploratory data analysis. Models that reflect hypothetical constructs via measurement variables. 14 / 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. 15 / 24 What does the communality of a variable in factor analysis measure? The sum of the squared factor loadings for the variable The uniqueness of the variable The proportion of variance in the variable explained by the factors The eigenvalue of the variable 16 / 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. Orthogonal rotation methods assume uncorrelated factors, while oblique methods allow for correlation between factors. There is no difference. 17 / 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 18 / 24 In factor analysis, what does the procedure primarily analyze? The correlation matrix The covariance matrix The regression coefficients The mean of the data 19 / 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. 20 / 24 What are factor loadings in factor analysis? The number of factors extracted The strength of the correlations between original variables and the factors Assessment values per person The factors themselves 21 / 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. 22 / 24 What statement(s) related to the KMO and MSA criterion are correct? MSA assesses the suitability of a single variable. There is no difference between the two criteria. Both criteria measure the same. KMO assesses the suitability of the correlation matrix. 23 / 24 How is the suitability of data for factor analysis typically evaluated? By calculating the correlation matrix By conducting a regression analysis By examining means and standard deviations By assessing inter-item reliability 24 / 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 can be combined into a common factor. They should be eliminated from the analysis. Your score is 0% Restart quiz Learn more…MethodsServiceAbout us ContactFeedbackOrder data etc. GeneralImprintPrivacy notice
