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