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 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 2 / 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 3 / 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 calculating the range By the coefficient of determination (R²) 4 / 23 What kind of variables are typically involved in contingency analysis? Categorical (nominal) variables Interval variables Ratio variables Continuous variables 5 / 23 What does the Chi-Square test assess in contingency analysis? Linearity of variables Association between categorical variables Difference in means Variance within groups 6 / 23 In contingency analysis, what does a contingency coefficient closer to 1 indicate? No association between variables Strong association between variables The variables are independent Weak association between variables 7 / 23 Which of the following scenarios is an example of using a contingency analysis? Calculating the variance of income across different cities Determining if there is an association between diet type and gender Comparing the average heights of men and women Estimating the relationship between advertising and sales 8 / 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. 9 / 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) 10 / 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 11 / 23 What is tested by the chi-square test in contingency analysis? Mean differences between groups Normal distribution of data Equality of variances Independence of variables 12 / 23 Which of the following is a step in the contingency analysis? Performing a T-test Calculating the mean difference Regression analysis Interpretation of cross tables 13 / 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 14 / 23 What does Goodman and Kruskal’s tau measure in the context of contingency analysis? The linear relationship between two variables The difference in means between two groups The strength of association based on marginal probabilities The correlation coefficient between two variables 15 / 23 Which method is an alternative to the chi-square test when sample sizes are small in contingency analysis? Fisher’s Exact Test T-test Pearson correlation ANOVA 16 / 23 What does a significant chi-square test indicate in the context of contingency analysis? The variables are normally distributed The variables are independent of each other The variables are dependent on each other The variables have equal variances 17 / 23 In which case would you use a contingency analysis? 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 To calculate the mean of a dataset 18 / 23 How is the phi coefficient calculated in contingency analysis? 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 Logarithm of the p-value Difference between observed and expected values 19 / 23 What would indicate a strong association in a contingency table analysis? Zero degrees of freedom Uniform distribution across the table Low chi-square value High residuals between observed and expected counts 20 / 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 21 / 23 Fill in the gap. “The Phi coefficient, contingency coefficient, Cramer’s V, Goodmann and Kruskal’s lambda and tau coefficient assess …” Check 22 / 23 Which statistic measures the strength of association in a contingency table? Beta coefficient T-statistic F-statistic Phi coefficient 23 / 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. Your score is 0% Restart quiz Learn more…MethodsServiceAbout us ContactFeedbackOrder data etc. GeneralImprintPrivacy notice
