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? Through the standard error By the coefficient of determination (R²) By calculating the range Using measures like Cramer's V and the contingency coefficient 2 / 23 In contingency analysis, what does a contingency coefficient closer to 1 indicate? The variables are independent Weak association between variables No association between variables Strong association between variables 3 / 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 4 / 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. 5 / 23 Which measure is used to assess the strength of association between variables in a contingency table? Cramer's V Mean squared error Standard deviation Chi-square statistic 6 / 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 * Number of columns (Number of rows + 1) * (Number of columns + 1) 7 / 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 independent of each other The variables are dependent on each other 8 / 23 Which method is an alternative to the chi-square test when sample sizes are small in contingency analysis? Fisher’s Exact Test ANOVA T-test Pearson correlation 9 / 23 What does the Chi-Square test assess in contingency analysis? Variance within groups Linearity of variables Association between categorical variables Difference in means 10 / 23 What is the primary purpose of applying the Yates’ Correction in the Chi-squared test? To increase the power of the test To handle missing data To correct for overdispersion To adjust for small sample sizes 11 / 23 Which statistic measures the strength of association in a contingency table? Phi coefficient T-statistic F-statistic Beta coefficient 12 / 23 Which of the following scenarios is an example of using a contingency analysis? 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 Comparing the average heights of men and women 13 / 23 Fill in the gap. “The Phi coefficient, contingency coefficient, Cramer’s V, Goodmann and Kruskal’s lambda and tau coefficient assess …” Check 14 / 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 15 / 23 What would indicate a strong association in a contingency table analysis? Zero degrees of freedom High residuals between observed and expected counts Low chi-square value Uniform distribution across the table 16 / 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. 17 / 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 Difference between observed and expected values Sum of the product of row and column totals divided by the grand total 18 / 23 What kind of variables are typically involved in contingency analysis? Continuous variables Interval variables Categorical (nominal) variables Ratio variables 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 linear relationship between two variables The strength of association based on marginal probabilities 20 / 23 Which measure is not based on the chi-square statistic for assessing the strength of association? Goodman and Kruskal’s lambda Phi coefficient Cramer's V Contingency coefficient 21 / 23 What is tested by the chi-square test in contingency analysis? Equality of variances Normal distribution of data Independence of variables Mean differences between groups 22 / 23 What is the purpose of creating a cross table in contingency analysis? To visualize the correlation between variables To display the joint distribution of two categorical variables To analyze the relationship between two continuous variables To compare the means of different samples 23 / 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 Your score is 0% Restart quiz Learn more…MethodsServiceAbout us ContactFeedbackOrder data etc. GeneralImprintPrivacy notice
