Test your knowledge.Receive immediate feedback.You find all answers in the book. Quiz | Discriminant Analysis /26 11 Quiz | Discriminant Analysis 1 / 26 “The number of describing variables should be … than the number of groups.” larger the same smaller 2 / 26 How are variables entered into a model in stepwise discriminant analysis? In order of their ability to reduce overall Wilks' lambda Based on their correlation with the dependent variable Randomly until all variables are used Simultaneously 3 / 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 4 / 26 What is one method that is used in discriminant analysis to identify variables that best separate groups? Principal component analysis Cluster analysis Linear regression Stepwise estimation procedure 5 / 26 What is a use of discriminant analysis in business? To calculate the profitability of investment options To forecast economic trends To measure employee satisfaction To classify companies into performance categories 6 / 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 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 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 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 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 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 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 13 / 26 What is a significant criterion for evaluating the quality of a discriminant function in discriminant analysis? The maximum value of the discriminant criterion, also known as eigenvalue The discriminant coefficients must all be positive The minimum value of the discriminant criterion, also known as eigenvalue The discriminant function must correctly classify all observations 14 / 26 Which coefficient does not affect the discriminant criterion? discriminant coefficients b constant term b0 15 / 26 What is the primary purpose of discriminant analysis? To identify independent variables To establish a relationship between a single categorical dependent variable and several metric independent variables To predict continuous outcomes To classify categorical independent variables 16 / 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. 17 / 26 How is the effectiveness of a discriminant function assessed? By determining the linear relationships between all variables By comparing the observed group memberships with those predicted by the function By the range of the independent variables By the number of groups in the analysis 18 / 26 In discriminant analysis, how is the significance of discriminant functions usually tested? Chi-square tests T-tests Regression analysis ANOVA 19 / 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 determine the weight of each variable They represent the variance of each group 20 / 26 In discriminant analysis, what are the independent variables usually required to be? None of the above Nominally scaled Metrically scaled Ordinally scaled 21 / 26 What is a 'grouping variable' in discriminant analysis? A variable that reflects the group an observation belongs to A variable that identifies a metric attribute A continuous variable A dependent metric variable 22 / 26 What is Wilks' lambda used for in discriminant analysis? To assess the multicollinearity among predictors To measure the proportion of variance explained by the discriminants To calculate the eigenvalues for each discriminant function To determine the overall significance of the discriminants 23 / 26 In discriminant analysis, what represents the group an observation belongs to? Metric variable Categorical variable Grouping variable Dependent variable 24 / 26 Which of the following is a common assumption in discriminant analysis? Variables are independent of each other The dependent variable is continuous Independent Variables are normally distributed Groups have equal sample sizes 25 / 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 exponential It is linear 26 / 26 How many groups are considered if referred to as "multi-group discriminant analysis"? Three or more groups Not specified Two groups One group Your score is 0% Restart quiz Learn more…MethodsServiceAbout us ContactFeedbackOrder data etc. GeneralImprintPrivacy notice
