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