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