Test your knowledge.Receive immediate feedback.You find all answers in the book. Quiz | Contingency Analysis /23 69 Quiz | Contingency Analysis 1 / 23 Cramer’s V reaches the value 1, if ... a variable is completely determined by the other variable. a variable is partly determined by the other variable. 2 / 23 Which measure is used to assess the strength of association between variables in a contingency table? Mean squared error Standard deviation Cramer's V Chi-square statistic 3 / 23 Which method is an alternative to the chi-square test when sample sizes are small in contingency analysis? Pearson correlation ANOVA T-test Fisher’s Exact Test 4 / 23 How are degrees of freedom calculated in a chi-square test for a contingency table? Number of rows * Number of columns (Number of rows + 1) * (Number of columns + 1) (Number of rows - 1) * (Number of columns - 1) Number of rows + Number of columns 5 / 23 What does the Chi-Square test assess in contingency analysis? Difference in means Linearity of variables Variance within groups Association between categorical variables 6 / 23 What is the purpose of creating a cross table in contingency analysis? To analyze the relationship between two continuous variables To visualize the correlation between variables To display the joint distribution of two categorical variables To compare the means of different samples 7 / 23 What does a significant chi-square test indicate in the context of contingency analysis? The variables have equal variances The variables are dependent on each other The variables are independent of each other The variables are normally distributed 8 / 23 Which of the following scenarios is an example of using a contingency analysis? Calculating the variance of income across different cities Determining if there is an association between diet type and gender Estimating the relationship between advertising and sales Comparing the average heights of men and women 9 / 23 What does Goodman and Kruskal’s tau measure in the context of contingency analysis? The correlation coefficient between two variables The strength of association based on marginal probabilities The linear relationship between two variables The difference in means between two groups 10 / 23 Which of the following is a step in the contingency analysis? Performing a T-test Regression analysis Interpretation of cross tables Calculating the mean difference 11 / 23 What is tested by the chi-square test in contingency analysis? Mean differences between groups Independence of variables Normal distribution of data Equality of variances 12 / 23 Which statistic measures the strength of association in a contingency table? Beta coefficient Phi coefficient T-statistic F-statistic 13 / 23 What is a critical assumption for the validity of the chi-square test in contingency tables? No cell should have an observed count less than 5 Variables must be continuous All cells must have observations 20% of the cells must have 5 or more observations 14 / 23 What does a large deviation between the observed and expected number of observations of two variables indicate? The variables are probably dependent. The variables are probably independent. 15 / 23 What is the primary purpose of applying the Yates’ Correction in the Chi-squared test? To adjust for small sample sizes To correct for overdispersion To handle missing data To increase the power of the test 16 / 23 How is the phi coefficient calculated in contingency analysis? Logarithm of the p-value Square root of Chi-square value divided by the sample size Sum of the product of row and column totals divided by the grand total Difference between observed and expected values 17 / 23 In contingency analysis, what does a contingency coefficient closer to 1 indicate? No association between variables The variables are independent Strong association between variables Weak association between variables 18 / 23 Which measure is not based on the chi-square statistic for assessing the strength of association? Contingency coefficient Cramer's V Goodman and Kruskal’s lambda Phi coefficient 19 / 23 In which case would you use a contingency analysis? To calculate the mean of a dataset To check the independence between two categorical variables To determine if there is a correlation between two metric variables To find the standard deviation of a sample 20 / 23 Fill in the gap. “The Phi coefficient, contingency coefficient, Cramer’s V, Goodmann and Kruskal’s lambda and tau coefficient assess …” Check 21 / 23 What kind of variables are typically involved in contingency analysis? Ratio variables Continuous variables Categorical (nominal) variables Interval variables 22 / 23 How can the strength of the association in a contingency table be measured? By the coefficient of determination (R²) Through the standard error By calculating the range Using measures like Cramer's V and the contingency coefficient 23 / 23 What would indicate a strong association in a contingency table analysis? Uniform distribution across the table High residuals between observed and expected counts Zero degrees of freedom Low chi-square value Your score is 0% Restart quiz Learn more…MethodsServiceAbout us ContactFeedbackOrder data etc. GeneralImprintPrivacy notice
