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