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