Test your knowledge.Receive immediate feedback.You find all answers in the book. Quiz | Discriminant Analysis /26 11 Quiz | Discriminant Analysis 1 / 26 Which coefficient does not affect the discriminant criterion? discriminant coefficients b constant term b0 2 / 26 How many groups are considered if referred to as "multi-group discriminant analysis"? Two groups One group Not specified Three or more groups 3 / 26 We observe 43 respondents, whereas five are misclassified. What is the hit rate of the correctly specified group assignments? 88% 80% 83% 4 / 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 5 / 26 What does a small value of Wilks' lambda indicate in the context of discriminant analysis? High correlation between groups Poor fit of the model Low variance among groups Strong discriminatory power of the function 6 / 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 7 / 26 What is NOT a step in the discriminant analysis procedure? Classification of new observations Collecting qualitative data Estimating discriminant functions Testing the describing variables 8 / 26 What is the primary purpose of discriminant analysis? To establish a relationship between a single categorical dependent variable and several metric independent variables To predict continuous outcomes To classify categorical independent variables To identify independent variables 9 / 26 “The number of describing variables should be … than the number of groups.” larger smaller the same 10 / 26 Which discriminant analysis method is suitable when assumptions of equal covariance matrices are not met? Canonical discriminant analysis Linear discriminant analysis Quadratic discriminant analysis Regular discriminant analysis 11 / 26 How are variables entered into a model in stepwise discriminant analysis? Based on their correlation with the dependent variable In order of their ability to reduce overall Wilks' lambda Randomly until all variables are used Simultaneously 12 / 26 When using discriminant analysis, what is assumed about the relationship between the independent and dependent variables? It is linear It is nonlinear It is logarithmic It is exponential 13 / 26 What is a use of discriminant analysis in business? To forecast economic trends To classify companies into performance categories To calculate the profitability of investment options To measure employee satisfaction 14 / 26 In discriminant analysis, what represents the group an observation belongs to? Categorical variable Dependent variable Metric variable Grouping variable 15 / 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 16 / 26 “The larger SSb and the … SSw, the larger the value for the discriminant criterion, and the better are the groups separated.” smaller larger 17 / 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 has no indication for the separation of the groups. An increasing value of Wilk’s Lambda indicates a better separation of the groups. 18 / 26 How is the effectiveness of a discriminant function assessed? By the number of groups in the analysis By comparing the observed group memberships with those predicted by the function By determining the linear relationships between all variables By the range of the independent variables 19 / 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 20 / 26 What is one method that is used in discriminant analysis to identify variables that best separate groups? Principal component analysis Cluster analysis Stepwise estimation procedure Linear regression 21 / 26 What is a significant criterion for evaluating the quality of a discriminant function in discriminant analysis? The discriminant function must correctly classify all observations The maximum value of the discriminant criterion, also known as eigenvalue The minimum value of the discriminant criterion, also known as eigenvalue The discriminant coefficients must all be positive 22 / 26 In discriminant analysis, how is the significance of discriminant functions usually tested? ANOVA Chi-square tests Regression analysis T-tests 23 / 26 In discriminant analysis, what are the independent variables usually required to be? None of the above Nominally scaled Metrically scaled Ordinally scaled 24 / 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 variable with the least variance within the group The most central variable in the analysis The median of all cases in a group 25 / 26 What does the Box's M test check for in discriminant analysis? Independence of variables Accuracy of classification Normality of the data Equality of within-group variance-covariance matrices 26 / 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 dependent metric variable A continuous variable Your score is 0% Restart quiz Learn more…MethodsServiceAbout us ContactFeedbackOrder data etc. GeneralImprintPrivacy notice
