4.2.3.3.1 Sign test and probability, significance and errors Quiz: AQA Psychology, Unit 2

The 20 questions

1. What type of design is the sign test typically used with?

   • Independent groups with interval data only
   • Repeated measures or matched pairs, where each participant gives two related scores
   • Case studies analysed qualitatively
   • Correlational designs measuring two continuous variables

2. Why is the sign test described as a non-parametric test?

   • It makes no assumption that the data follow a normal distribution
   • It requires a sample of at least 100 participants
   • It can only be used with ratio level data
   • It always gives a more powerful result than a related t-test

3. In the sign test, what is recorded for each participant?

   • The exact numerical difference between the two scores
   • The rank of each participant's total score
   • Whether the difference between the two scores is positive, negative or zero
   • The mean of the two conditions for that participant

4. In the sign test, how are participants with no difference between their two scores treated?

   • They are removed from the analysis, so N is reduced
   • They are counted as positive differences
   • They are counted as negative differences
   • They are split equally between the positive and negative categories

5. What is a Type I error?

   • Failing to randomise participants to conditions
   • Using the wrong test for the level of measurement
   • Rejecting the null hypothesis when it is actually true, a false positive
   • Accepting the null hypothesis when it is actually false, a false negative

6. What is a Type II error?

   • Rejecting the null hypothesis when it is actually true
   • Using a one-tailed test when a two-tailed test was predicted
   • Accepting the null hypothesis when a real effect exists, a false negative
   • Setting the significance level at 0.05 rather than 0.01

7. What significance level is conventionally used in psychology?

   • 0.5 (50%)
   • 0.001 (0.1%)
   • 0.05 (5%)
   • 0.95 (95%)

8. In a sign test, 10 participants are tested. Eight show an increase and two show a decrease, with no zero differences. What is S, the smaller number of signs?

   • 8
   • 10
   • 5
   • 2

9. A sign test with N = 10 gives S = 2. The critical value for a two-tailed test at the 0.05 level is 1. Is the result significant?

   • Yes, because S is less than the critical value
   • Yes, because S is greater than the critical value
   • No, because S is less than the critical value
   • No, because S is greater than the critical value

10. The same data (N = 10, S = 2) are analysed with a one-tailed test at the 0.05 level, where the critical value is 2. What is the conclusion?

    • Significant, because N is 10
    • Not significant, because there were no zero differences
    • Not significant, because S is larger than 2
    • Significant, because S equals the critical value of 2

11. A study has 12 participants and one shows no change between conditions. What is N for the sign test?

    • 12
    • 1
    • 10
    • 11

12. Which observed value of S, with N = 10, would be significant on a one-tailed test at the 0.05 level, where the critical value is 2?

    • S = 3
    • S = 5
    • S = 4
    • S = 2

13. A sign test has 15 non-zero differences, with 11 positive and 4 negative. What is S?

    • 7
    • 15
    • 11
    • 4

14. A psychologist tests the same students before and after a revision programme, using scores that are ranked, not interval. Which test is suitable?

    • Spearman's rho
    • Sign test
    • Chi-squared test
    • Unrelated t-test

15. A researcher lowers the significance level from 0.05 to 0.01. What is the effect on the risk of a Type I error?

    • It becomes zero, because the test is now exact
    • It is reduced, because the criterion for significance is stricter
    • It is unchanged, because it depends only on sample size
    • It is increased, because more results will become significant

16. A sign test shows a significant result, but the effect is later shown not to exist. Which error has occurred?

    • A Type I error
    • A ceiling effect
    • A demand characteristic
    • A Type II error

17. Why might a researcher choose a two-tailed test rather than a one-tailed test?

    • A two-tailed test allows the researcher to ignore zero differences
    • A two-tailed test is always more powerful than a one-tailed test
    • There is no clear directional prediction, so an effect in either direction should be detectable
    • A one-tailed test always has a higher chance of a Type I error

18. A sign test with 10 participants gives S = 4. The one-tailed critical value at 0.05 is 2. What is the correct conclusion?

    • Significant, because S is an even number
    • Significant, so the null hypothesis is rejected
    • Not significant, so the null hypothesis is retained
    • Not significant, because the sign test cannot be used with N = 10

19. Lowering the significance level reduces the risk of one error type but increases the risk of another. Which is the correct trade-off?

    • Lowering alpha increases false positives but reduces false negatives
    • Lowering alpha reduces both Type I and Type II errors equally
    • Lowering alpha has no effect on either type of error
    • Lowering alpha reduces false positives but increases the risk of false negatives

20. Which is a strength of the sign test?

    • It can only be used with independent groups
    • It uses the actual size of each difference, so it is more precise than a related t-test
    • It is simple to calculate and does not assume normally distributed data
    • It always detects small effects better than parametric tests

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