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