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