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