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