Test your knowledge.Receive immediate feedback.You find all answers in the book. Quiz | Factor Analysis /24 59 Quiz | Factor Analysis 1 / 24 What does a negative factor score represent in factor analysis? 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. 2 / 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 3 / 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. 4 / 24 How is the suitability of data for factor analysis typically evaluated? By assessing inter-item reliability By examining means and standard deviations By calculating the correlation matrix By conducting a regression analysis 5 / 24 What does CFA refer to when it mentions "reflective measurement models"? Models that reflect hypothetical constructs via measurement variables. Models that reflect the data structure without assumptions. Models that involve exploratory data analysis. Models that are highly complex and difficult to interpret. 6 / 24 What are factor loadings in factor analysis? Assessment values per person The number of factors extracted The factors themselves The strength of the correlations between original variables and the factors 7 / 24 In a factor analysis, what do the factor scores represent? Number of factors extracted Original variables Values per person on the latent factors Strength of correlations 8 / 24 What is the difference between communality and eigenvalue? Check 9 / 24 In factor analysis, what do factor loadings (ajq) represent? The correlation between an observed variable and the extracted factor The number of observations (cases) The sum of the squared factor loadings The variance of the observed variables 10 / 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 11 / 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 eliminate unique variance in observed variables To reduce the dimensionality of data 12 / 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 using regression analysis on factor loadings By multiplying factor loadings by the number of variables By calculating the mean of the high-loading variables for each factor 13 / 24 What does the communality of a variable in factor analysis measure? The proportion of variance in the variable explained by the factors The uniqueness of the variable The sum of the squared factor loadings for the variable The eigenvalue of the variable 14 / 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 degrees of freedom are low When the correlation matrix is not an identity matrix When the variables in the sample are uncorrelated 15 / 24 What is the H0 of the Bartlett test of sphericity? The variables in the population are correlated. The variables in the population are uncorrelated. The variables in the sample are uncorrelated. The variables in the sample are correlated. 16 / 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. 17 / 24 What does the fundamental theorem of factor analysis state? It calculates the variance of factors It defines the correlation matrix. It explains how to standardize data. It relates observed data to unobserved factors. 18 / 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 an average rating on the factor. An object has the highest rating on the factor. An object is rated below average on the factor. 19 / 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 are the result of common causes (factors). They have no correlation. 20 / 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. 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. Orthogonal rotation methods assume uncorrelated factors, while oblique methods allow for correlation between factors. There is no difference. 22 / 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 reduce a large number of correlating variables to a fewer number of factors To decrease the number of factors 23 / 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 3: Interpreting the factors Step 2: Extracting the factors 24 / 24 In factor analysis, what does the procedure primarily analyze? The regression coefficients The mean of the data The correlation matrix The covariance matrix Your score is 0% Restart quiz Learn more…MethodsServiceAbout us ContactFeedbackOrder data etc. GeneralImprintPrivacy notice
