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