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