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