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