Test your knowledge.Receive immediate feedback.You find all answers in the book. Quiz | Factor Analysis /24 59 Quiz | Factor Analysis 1 / 24 When is a correlation matrix considered suitable for factor analysis according to the Bartlett test of sphericity? 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 When the degrees of freedom are low 2 / 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 3: Interpreting the factors Step 2: Extracting the factors Step 1: Checking data suitability 3 / 24 What does the fundamental theorem of factor analysis state? It calculates the variance of factors It relates observed data to unobserved factors. It defines the correlation matrix. It explains how to standardize data. 4 / 24 What does a high correlation between two variables indicate in factor analysis? They are unsuitable for factor analysis. They should be eliminated from the analysis. They can be combined into a common factor. They are weakly correlated with other variables. 5 / 24 How is the suitability of data for factor analysis typically evaluated? By conducting a regression analysis By examining means and standard deviations By calculating the correlation matrix By assessing inter-item reliability 6 / 24 What are factor loadings in factor analysis? The number of factors extracted The strength of the correlations between original variables and the factors The factors themselves Assessment values per person 7 / 24 What does the communality of a variable in factor analysis measure? The proportion of variance in the variable explained by the factors The sum of the squared factor loadings for the variable The uniqueness of the variable The eigenvalue of the variable 8 / 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). 9 / 24 What statement(s) related to the KMO and MSA criterion are correct? There is no difference between the two criteria. Both criteria measure the same. MSA assesses the suitability of a single variable. KMO assesses the suitability of the correlation matrix. 10 / 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 11 / 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 calculate the eigenvalues of factors To determine the factor loadings 12 / 24 In factor analysis, what do factor loadings (ajq) represent? The sum of the squared factor loadings The number of observations (cases) The correlation between an observed variable and the extracted factor The variance of the observed variables 13 / 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. 14 / 24 What is the difference between communality and eigenvalue? Check 15 / 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. 16 / 24 What is the H0 of the Bartlett test of sphericity? The variables in the sample are correlated. The variables in the population are uncorrelated. The variables in the sample are uncorrelated. The variables in the population are correlated. 17 / 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 18 / 24 What does CFA refer to when it mentions "reflective measurement models"? Models that reflect the data structure without assumptions. Models that involve exploratory data analysis. Models that are highly complex and difficult to interpret. Models that reflect hypothetical constructs via measurement variables. 19 / 24 How are summated scales calculated for factor scores in factor analysis? By multiplying factor loadings by the number of variables 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 using regression analysis on factor loadings 20 / 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 21 / 24 Explain why the variable "I have difficulty in imagining Calvé in my mind” has a negative factor loading for factor 1. The item is a reverse coded item, and has, thus, a negative factor loading. This must be a mistake. Factor loadings need to be positive. 22 / 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. 23 / 24 In factor analysis, what does the procedure primarily analyze? The mean of the data The correlation matrix The covariance matrix The regression coefficients 24 / 24 What is one of the main objectives of factor analysis? 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 To increase the variance-covariance matrix Your score is 0% Restart quiz Learn more…MethodsServiceAbout us ContactFeedbackOrder data etc. GeneralImprintPrivacy notice
