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