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