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