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