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 primary purpose of applying the Yates’ Correction in the Chi-squared test? To increase the power of the test To correct for overdispersion To adjust for small sample sizes To handle missing data 2 / 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 3 / 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 Variables must be continuous No cell should have an observed count less than 5 4 / 23 What would indicate a strong association in a contingency table analysis? Zero degrees of freedom High residuals between observed and expected counts Low chi-square value Uniform distribution across the table 5 / 23 Which of the following is a step in the contingency analysis? Interpretation of cross tables Performing a T-test Regression analysis Calculating the mean difference 6 / 23 Which method is an alternative to the chi-square test when sample sizes are small in contingency analysis? Fisher’s Exact Test ANOVA Pearson correlation T-test 7 / 23 What does Goodman and Kruskal’s tau measure in the context of contingency analysis? The strength of association based on marginal probabilities The correlation coefficient between two variables The difference in means between two groups The linear relationship between two variables 8 / 23 Which measure is used to assess the strength of association between variables in a contingency table? Standard deviation Chi-square statistic Cramer's V Mean squared error 9 / 23 Which of the following scenarios is an example of using a contingency analysis? Comparing the average heights of men and women 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 10 / 23 Which measure is not based on the chi-square statistic for assessing the strength of association? Phi coefficient Contingency coefficient Goodman and Kruskal’s lambda Cramer's V 11 / 23 What does a significant chi-square test indicate in the context of contingency analysis? The variables have equal variances The variables are dependent on each other The variables are normally distributed The variables are independent of each other 12 / 23 What does the Chi-Square test assess in contingency analysis? Variance within groups Association between categorical variables Linearity of variables Difference in means 13 / 23 What kind of variables are typically involved in contingency analysis? Interval variables Continuous variables Categorical (nominal) variables Ratio variables 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 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) 16 / 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 17 / 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 18 / 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 19 / 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. 20 / 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 Sum of the product of row and column totals divided by the grand total Logarithm of the p-value 21 / 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. 22 / 23 In which case would you use a contingency analysis? To calculate the mean of a dataset To find the standard deviation of a sample To check the independence between two categorical variables To determine if there is a correlation between two metric variables 23 / 23 Which statistic measures the strength of association in a contingency table? T-statistic Phi coefficient F-statistic Beta coefficient Your score is 0% Restart quiz Learn more…MethodsServiceAbout us ContactFeedbackOrder data etc. GeneralImprintPrivacy notice
