Lesson 9.1.5

9.1.5 Inferential statistics and levels of significance Quiz: Pearson Edexcel Psychology, Unit 9

20 questions

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Lesson 9.1.5, Inferential statistics and levels of significance: 20 multiple choice questions for the Pearson Edexcel Psychology (9PS0), Unit 9: Psychological skills, written with Revision Ninja.

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The 20 questions

  1. Which test is used to examine differences between two independent groups using ordinal data?

    • Spearman's rho
    • Chi-squared test of association
    • Mann-Whitney U
    • Wilcoxon signed-ranks

  2. Which test is appropriate for comparing two conditions measured on the same participants using ordinal data?

    • Spearman's rho
    • Mann-Whitney U
    • Chi-squared test
    • Wilcoxon signed-ranks

  3. Which test is used to measure the strength and direction of a relationship between two co-variables measured on ordinal scales?

    • Spearman's rho
    • Chi-squared test of difference
    • Mann-Whitney U
    • Wilcoxon signed-ranks

  4. Which test should be used to examine the difference in frequencies of categories, such as the number of people choosing each option in two conditions?

    • Spearman's rho
    • Wilcoxon signed-ranks
    • Chi-squared test of difference
    • Mann-Whitney U

  5. What are the four levels of measurement, in order from least to most informative?

    • Interval, ratio, nominal, ordinal
    • Nominal, ordinal, interval, ratio
    • Ratio, interval, ordinal, nominal
    • Ordinal, nominal, ratio, interval

  6. Which level of measurement describes data such as a ranking of runners from first to last, where the gaps between ranks may not be equal?

    • Interval
    • Ratio
    • Ordinal
    • Nominal

  7. A one-tailed test is used when:

    • A directional hypothesis has been stated
    • The data are qualitative
    • The sample is randomly selected
    • No direction of effect has been predicted

  8. A researcher's observed value of a test is 4.10 and the critical value at p≤.05 is 3.84. What is the conclusion?

    • The result is significant, so the null hypothesis is rejected
    • The observed value cannot be compared with the critical value
    • The result is not significant, so the null hypothesis is retained
    • The critical value is wrong

  9. A researcher sets the significance level at p≤.05 before the study. What does this mean?

    • The researcher accepts a 5 per cent risk of rejecting the null hypothesis when it is actually true
    • The researcher will reject the null hypothesis only if the sample is smaller than 5
    • The researcher is certain that 95 per cent of the sample is correct
    • The researcher has proven the alternate hypothesis

  10. A researcher reports p=.03 for a test. What does this mean in relation to a p≤.05 level?

    • The result proves the hypothesis is true
    • The result is significant at the .05 level
    • The result is not significant at the .05 level
    • The result is significant at the .01 level only

  11. A researcher finds p=.07 with a significance level of .05. Which decision is correct?

    • Reject the null hypothesis, because .07 is greater than .05
    • Accept the alternate hypothesis as proven
    • Retain the null hypothesis, because the result is not significant at the .05 level
    • Change the significance level to .10 and reject the null hypothesis

  12. What is a Type I error?

    • Retaining the null hypothesis when it is actually false
    • Recording data incorrectly during the study
    • Rejecting the null hypothesis when it is actually true
    • Using the wrong test for the level of data

  13. What is a Type II error?

    • Rejecting the null hypothesis when it is actually true
    • Using a two-tailed test when a one-tailed test was required
    • Failing to record demographic data
    • Retaining the null hypothesis when it is actually false

  14. Which change would reduce the chance of a Type I error?

    • Removing the critical value from the analysis
    • Using a stricter significance level such as .01
    • Using a smaller sample to make results more significant
    • Using a more lenient significance level such as .10

  15. Why is the choice of statistical test linked to the level of measurement?

    • Tests can be used interchangeably for any data
    • Each test assumes particular types of data, so using the wrong test can produce misleading results
    • Level of measurement only affects qualitative research
    • Level of measurement determines the colour of the graph only

  16. A researcher says the result is significant because the observed value is larger than the critical value. For a test where a larger observed value means a stronger effect, is this correct?

    • No, critical values are not used in psychology
    • Yes, this is correct, because a significant result requires the observed value to meet or exceed the critical value
    • No, the observed value must always be negative
    • No, a significant result requires the observed value to be smaller than the critical value

  17. A researcher uses a two-tailed test. What does this mean in terms of the hypothesis?

    • The hypothesis is non-directional, predicting a difference without stating its direction
    • The hypothesis is directional, predicting a particular direction
    • The data are qualitative and must be analysed in two stages
    • The sample has two groups only

  18. A chi-squared observed value is 7.20 with 2 degrees of freedom. The critical value at p≤.05 is 5.99. Which conclusion is correct?

    • The result is not significant, because 7.20 is larger than 5.99
    • The result is significant, because 7.20 is smaller than 5.99
    • The result is significant, because 7.20 is larger than 5.99
    • The result cannot be interpreted without a p value

  19. What does a significant result tell a researcher?

    • That the study has no limitations
    • That the result is true for every participant
    • That the observed result is unlikely to have occurred by chance if the null hypothesis were true
    • That the independent variable caused every change in the dependent variable

  20. A study with 200 participants finds a very small correlation that is statistically significant. Which evaluation point is most valid?

    • Significance proves that the variables are causally linked
    • A large sample always makes the effect important
    • Statistical significance does not necessarily mean the effect is large or practically important
    • Significance cannot be found in samples of this size

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