Test your knowledge.Receive immediate feedback.You find all answers in the book. Quiz | Discriminant Analysis /26 11 Quiz | Discriminant Analysis 1 / 26 Which coefficient does not affect the discriminant criterion? discriminant coefficients b constant term b0 2 / 26 In discriminant analysis, what represents the group an observation belongs to? Dependent variable Grouping variable Metric variable Categorical variable 3 / 26 “The number of describing variables should be … than the number of groups.” the same smaller larger 4 / 26 “The larger SSb and the … SSw, the larger the value for the discriminant criterion, and the better are the groups separated.” smaller larger 5 / 26 What is a significant criterion for evaluating the quality of a discriminant function in discriminant analysis? The minimum value of the discriminant criterion, also known as eigenvalue The maximum value of the discriminant criterion, also known as eigenvalue The discriminant coefficients must all be positive The discriminant function must correctly classify all observations 6 / 26 We observe 43 respondents, whereas five are misclassified. What is the hit rate of the correctly specified group assignments? 88% 83% 80% 7 / 26 Which discriminant analysis method is suitable when assumptions of equal covariance matrices are not met? Regular discriminant analysis Quadratic discriminant analysis Linear discriminant analysis Canonical discriminant analysis 8 / 26 In discriminant analysis, what are the independent variables usually required to be? Metrically scaled Nominally scaled Ordinally scaled None of the above 9 / 26 How are variables entered into a model in stepwise discriminant analysis? Based on their correlation with the dependent variable Simultaneously Randomly until all variables are used In order of their ability to reduce overall Wilks' lambda 10 / 26 What is Wilks' lambda used for in discriminant analysis? To calculate the eigenvalues for each discriminant function To measure the proportion of variance explained by the discriminants To assess the multicollinearity among predictors To determine the overall significance of the discriminants 11 / 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 12 / 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 13 / 26 In discriminant analysis, how is the significance of discriminant functions usually tested? T-tests Regression analysis Chi-square tests ANOVA 14 / 26 What does the Box's M test check for in discriminant analysis? Normality of the data Equality of within-group variance-covariance matrices Independence of variables Accuracy of classification 15 / 26 When using discriminant analysis, what is assumed about the relationship between the independent and dependent variables? It is logarithmic It is exponential It is linear It is nonlinear 16 / 26 What is NOT a step in the discriminant analysis procedure? Testing the describing variables Collecting qualitative data Estimating discriminant functions Classification of new observations 17 / 26 What is one method that is used in discriminant analysis to identify variables that best separate groups? Stepwise estimation procedure Principal component analysis Cluster analysis Linear regression 18 / 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 the range of the independent variables By determining the linear relationships between all variables 19 / 26 What statistical test is used if we want to know whether two groups differ significantly concerning one variable? Chi-square test ANOVA Independent samples t-test Pearson correlation 20 / 26 What is a use of discriminant analysis in business? To measure employee satisfaction To calculate the profitability of investment options To forecast economic trends To classify companies into performance categories 21 / 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 22 / 26 What does an increasing value of Wilk’s Lambda indicate? 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 worse separation of the groups. An increasing value of Wilk’s Lambda indicates a better separation of the groups. 23 / 26 How many groups are considered if referred to as "multi-group discriminant analysis"? Three or more groups One group Two groups Not specified 24 / 26 In the context of discriminant analysis, what represents the centroid of a group? The median of all cases in a group The variable with the least variance within the group The most central variable in the analysis The mean value for the discriminant variable of the group 25 / 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 Low variance among groups Strong discriminatory power of the function 26 / 26 What role do eigenvalues play in discriminant analysis? They represent the variance of each group They determine the weight of each variable They are used to compute Wilks' lambda They indicate the maximum value of the discriminant criterion Your score is 0% Restart quiz Learn more…MethodsServiceAbout us ContactFeedbackOrder data etc. GeneralImprintPrivacy notice
