Test your knowledge.Receive immediate feedback.You find all answers in the book. Quiz | Discriminant Analysis /26 11 Quiz | Discriminant Analysis 1 / 26 Which discriminant analysis method is suitable when assumptions of equal covariance matrices are not met? Quadratic discriminant analysis Canonical discriminant analysis Linear discriminant analysis Regular discriminant analysis 2 / 26 When using discriminant analysis, what is assumed about the relationship between the independent and dependent variables? It is nonlinear It is logarithmic It is exponential It is linear 3 / 26 What does a small value of Wilks' lambda indicate in the context of discriminant analysis? Poor fit of the model High correlation between groups Strong discriminatory power of the function Low variance among groups 4 / 26 What is the primary purpose of discriminant analysis? To predict continuous outcomes To establish a relationship between a single categorical dependent variable and several metric independent variables To identify independent variables To classify categorical independent variables 5 / 26 In discriminant analysis, how is the significance of discriminant functions usually tested? Chi-square tests Regression analysis ANOVA T-tests 6 / 26 What is Wilks' lambda used for in discriminant analysis? To calculate the eigenvalues for each discriminant function To assess the multicollinearity among predictors To determine the overall significance of the discriminants To measure the proportion of variance explained by the discriminants 7 / 26 In the context of discriminant analysis, what represents the centroid of a group? The median of all cases in a group The mean value for the discriminant variable of the group The variable with the least variance within the group The most central variable in the analysis 8 / 26 What is one method that is used in discriminant analysis to identify variables that best separate groups? Linear regression Principal component analysis Cluster analysis Stepwise estimation procedure 9 / 26 How is the effectiveness of a discriminant function assessed? By comparing the observed group memberships with those predicted by the function By the number of groups in the analysis By determining the linear relationships between all variables By the range of the independent variables 10 / 26 In discriminant analysis, what are the independent variables usually required to be? Nominally scaled Ordinally scaled None of the above Metrically scaled 11 / 26 What is NOT a step in the discriminant analysis procedure? Collecting qualitative data Classification of new observations Testing the describing variables Estimating discriminant functions 12 / 26 What is a 'grouping variable' in discriminant analysis? A dependent metric variable A variable that identifies a metric attribute A continuous variable A variable that reflects the group an observation belongs to 13 / 26 What is a use of discriminant analysis in business? To measure employee satisfaction To classify companies into performance categories To calculate the profitability of investment options To forecast economic trends 14 / 26 What does an increasing value of Wilk’s Lambda indicate? An increasing value of Wilk’s Lambda indicates a worse separation of the groups. An increasing value of Wilk’s Lambda has no indication for the separation of the groups. An increasing value of Wilk’s Lambda indicates a better separation of the groups. 15 / 26 We observe 43 respondents, whereas five are misclassified. What is the hit rate of the correctly specified group assignments? 80% 88% 83% 16 / 26 Which coefficient does not affect the discriminant criterion? constant term b0 discriminant coefficients b 17 / 26 How are variables entered into a model in stepwise discriminant analysis? Randomly until all variables are used In order of their ability to reduce overall Wilks' lambda Based on their correlation with the dependent variable Simultaneously 18 / 26 What is a significant criterion for evaluating the quality of a discriminant function in discriminant analysis? The maximum value of the discriminant criterion, also known as eigenvalue The minimum value of the discriminant criterion, also known as eigenvalue The discriminant coefficients must all be positive The discriminant function must correctly classify all observations 19 / 26 What does the Box's M test check for in discriminant analysis? Normality of the data Independence of variables Accuracy of classification Equality of within-group variance-covariance matrices 20 / 26 “The number of describing variables should be … than the number of groups.” smaller the same larger 21 / 26 Which of the following is a common assumption in discriminant analysis? Independent Variables are normally distributed Variables are independent of each other The dependent variable is continuous Groups have equal sample sizes 22 / 26 In discriminant analysis, what represents the group an observation belongs to? Metric variable Grouping variable Categorical variable Dependent variable 23 / 26 How many groups are considered if referred to as "multi-group discriminant analysis"? Not specified Three or more groups Two groups One group 24 / 26 “The larger SSb and the … SSw, the larger the value for the discriminant criterion, and the better are the groups separated.” smaller larger 25 / 26 What statistical test is used if we want to know whether two groups differ significantly concerning one variable? ANOVA Independent samples t-test Pearson correlation Chi-square test 26 / 26 What role do eigenvalues play in discriminant analysis? They indicate the maximum value of the discriminant criterion They determine the weight of each variable They represent the variance of each group They are used to compute Wilks' lambda Your score is 0% Restart quiz Learn more…MethodsServiceAbout us ContactFeedbackOrder data etc. GeneralImprintPrivacy notice
