Significance, Parametric vs Non-parametric & t-test

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Welcome! 3.2 Significance, Parametric vs Non-parametric & t-test — Test 1 — 20 questions, CSIR-NET style.

What this test covers

  • Levels of significance & p-values
  • Parametric vs non-parametric tests
  • Student's t-test (one-sample, two-sample, paired)
  • Non-parametric alternatives & the t-distribution

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3.2 Significance, Parametric vs Non-parametric & t-test — Test 1
Q1. The level of significance (α) in a test is:✓ The probability threshold for rejecting the null hypothesis
Q2. The p-value of a test is:✓ The probability of obtaining results at least as extreme as observed, if H0 is true
Q3. If the p-value is less than the significance level α, the decision is to:✓ Reject the null hypothesis
Q4. Parametric tests differ from non-parametric tests mainly in that parametric tests:✓ Assume the data follow a particular distribution (often normal)
Q5. Non-parametric tests are preferred when:✓ Data are ordinal or do not meet distributional assumptions
Q6. Student's t-test is used to:✓ Compare means, especially for small samples
Q7. A paired t-test is appropriate when:✓ The two sets of measurements are related (e.g. before and after on the same subjects)
Q8. An independent (two-sample) t-test compares the means of:✓ Two separate, unrelated groups
Q9. The t-test is classified as a ____ test.✓ Parametric
Q10. A non-parametric alternative to the independent t-test is the:✓ Mann-Whitney U test
Q11. Degrees of freedom in a t-test are related to:✓ The sample size(s)
Q12. A result is described as 'statistically significant' when:✓ The p-value is below the chosen significance level
Q13. A one-tailed test differs from a two-tailed test in that a one-tailed test:✓ Tests for an effect in one specified direction only
Q14. A key assumption of the t-test is that the data are:✓ Approximately normally distributed
Q15. The critical value in a hypothesis test is:✓ The cut-off that the test statistic must exceed to reject H0
Q16. A one-sample t-test is used to compare:✓ A sample mean with a known or hypothesised value
Q17. Compared with parametric tests, non-parametric tests are generally:✓ More robust to assumption violations but sometimes less powerful
Q18. The t-distribution, compared with the normal distribution, has:✓ Heavier tails, especially for small samples
Q19. A smaller p-value provides:✓ Stronger evidence against the null hypothesis
Q20. Match each item with its description and select the correct option.✓ A-iii, B-i, C-iv, D-ii