Test your knowledge.Receive immediate feedback.You find all answers in the book. Quiz | Contingency Analysis /23 69 Quiz | Contingency Analysis 1 / 23 What kind of variables are typically involved in contingency analysis? Categorical (nominal) variables Continuous variables Interval variables Ratio variables 2 / 23 Which measure is not based on the chi-square statistic for assessing the strength of association? Contingency coefficient Goodman and Kruskal’s lambda Phi coefficient Cramer's V 3 / 23 What does the Chi-Square test assess in contingency analysis? Variance within groups Linearity of variables Difference in means Association between categorical variables 4 / 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 5 / 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. 6 / 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 Comparing the average heights of men and women Estimating the relationship between advertising and sales 7 / 23 Which measure is used to assess the strength of association between variables in a contingency table? Chi-square statistic Standard deviation Cramer's V Mean squared error 8 / 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 9 / 23 What does Goodman and Kruskal’s tau measure in the context of contingency analysis? The strength of association based on marginal probabilities The difference in means between two groups The correlation coefficient between two variables The linear relationship between two variables 10 / 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 11 / 23 Which of the following is a step in the contingency analysis? Interpretation of cross tables Performing a T-test Calculating the mean difference Regression analysis 12 / 23 What is the primary purpose of applying the Yates’ Correction in the Chi-squared test? To correct for overdispersion To increase the power of the test To handle missing data To adjust for small sample sizes 13 / 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) 14 / 23 What does a significant chi-square test indicate in the context of contingency analysis? The variables are dependent on each other The variables have equal variances The variables are normally distributed The variables are independent of each other 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 What would indicate a strong association in a contingency table analysis? High residuals between observed and expected counts Low chi-square value Uniform distribution across the table Zero degrees of freedom 17 / 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 No cell should have an observed count less than 5 Variables must be continuous All cells must have observations 18 / 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 19 / 23 How is the phi coefficient calculated in contingency analysis? 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 Logarithm of the p-value 20 / 23 In contingency analysis, what does a contingency coefficient closer to 1 indicate? Strong association between variables Weak association between variables No association between variables The variables are independent 21 / 23 Which statistic measures the strength of association in a contingency table? T-statistic Phi coefficient Beta coefficient F-statistic 22 / 23 In which case would you use a contingency analysis? To calculate the mean of a dataset To check the independence between two categorical variables To determine if there is a correlation between two metric variables To find the standard deviation of a sample 23 / 23 What does a large deviation between the observed and expected number of observations of two variables indicate? The variables are probably independent. 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