3.3 Analysis of Variance (ANOVA) & Chi-square Test — Test 1

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3.3 Analysis of Variance (ANOVA) & Chi-square Test — Test 1

Q1. Analysis of variance (ANOVA) is used to compare the means of:✓ Three or more groups simultaneously

Q2. The test statistic used in ANOVA is the:✓ F-ratio (F-statistic)

Q3. ANOVA works by partitioning the total variance into:✓ Between-group and within-group components

Q4. The null hypothesis in a one-way ANOVA states that:✓ All group means are equal

Q5. A key reason to use ANOVA instead of many separate t-tests is that multiple t-tests:✓ Inflate the overall Type I error rate

Q6. One-way ANOVA differs from two-way ANOVA in that one-way ANOVA involves:✓ A single factor (independent variable)

Q7. The chi-square (X²) test is primarily used for:✓ Categorical (frequency) data

Q8. The chi-square goodness-of-fit test assesses whether:✓ Observed frequencies match an expected distribution

Q9. The chi-square test of independence assesses whether:✓ Two categorical variables are associated

Q10. The chi-square statistic is calculated from:✓ The squared differences between observed and expected frequencies, divided by expected

Q11. A two-dimensional table of frequencies used in a chi-square test of independence is called a:✓ Contingency table

Q12. In ANOVA, a large F-ratio (well above 1) suggests that:✓ Between-group variability is large relative to within-group variability

Q13. A key assumption of ANOVA is that the groups have:✓ Approximately equal variances (homogeneity of variance)

Q14. The chi-square test is classified as a ____ test.✓ Non-parametric

Q15. In a chi-square test, the expected frequency for a cell (test of independence) is calculated from the:✓ Row total × column total ÷ grand total

Q16. ANOVA is classified as a ____ test.✓ Parametric

Q17. A significant chi-square result in a test of independence indicates that:✓ The two variables are likely associated, not independent

Q18. Degrees of freedom for a chi-square test of independence in an r × c table are:✓ (r − 1)(c − 1)

Q19. When a one-way ANOVA is significant, the next step is often to:✓ Perform post-hoc tests to find which groups differ

Q20. Match each test/term with its description and select the correct option.✓ A-ii, B-i, C-iv, D-iii