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
-
Which statistical test evaluates differences between two independent groups using ordinal data?
- Wilcoxon test
- Spearman's rank test
- Mann-Whitney U test
- Chi-squared test
-
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
-
Which statistical test assesses a relationship between two co-variables measured on ordinal scales?
- Spearman's rho
- Chi-squared test
- Mann-Whitney U
- Wilcoxon test
-
Which statistical test measures differences in categorical frequencies using nominal data?
- Spearman's rho
- Wilcoxon test
- Chi-squared test
- Mann-Whitney U
-
Which level of measurement provides the least informative, categorical type of data?
- Ordinal
- Nominal
- Ratio
- Interval
-
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
-
Which type of hypothesis requires a one-tailed statistical test?
- Directional hypothesis
- Alternative hypothesis
- Non-directional hypothesis
- Null hypothesis
-
An observed value of 4.10 exceeds a critical value of 3.84. What is the conclusion?
- Reject null hypothesis
- Accept null hypothesis
- Retain null hypothesis
- Result is non-significant
-
What is the maximum risk of making a Type I error at p <= 0.05?
- 5 per cent
- 50 per cent
- 10 per cent
- 1 per cent
-
A test calculates p = 0.03 against a threshold of p <= 0.05. How is this result described?
- Unreliable
- Statistically significant
- Inconclusive
- Not significant
-
A statistical test gives p = 0.07 at a p <= 0.05 significance level. What action should be taken?
- Reject null hypothesis
- Accept alternate hypothesis
- Retain null hypothesis
- Decrease sample size
-
What error occurs when a researcher wrongly rejects a true null hypothesis?
- Sampling error
- Standard error
- Type I error
- Type II error
-
What error occurs when a researcher wrongly retains a false null hypothesis?
- Standard error
- Experimental error
- Type I error
- Type II error
-
Which significance level reduces the chance of making a Type I error compared to p <= 0.05?
- p <= 0.10
- p <= 0.01
- p <= 0.20
- p <= 0.15
-
Which factor, alongside research design and hypothesis type, dictates the choice of statistical test?
- Standard deviation
- Level of measurement
- Participant gender
- Sample size
-
For most statistical tests, what must the observed value do relative to the critical value for significance?
- Equal zero
- Exceed critical value
- Be smaller than
- Match p-value
-
Which type of hypothesis requires a two-tailed statistical test?
- Non-directional hypothesis
- Causal hypothesis
- Directional hypothesis
- Null hypothesis
-
A Chi-squared calculated value is 7.20 and critical value is 5.99. What is the statistical conclusion?
- Not significant
- Retain null hypothesis
- Statistically significant
- Type II error
-
What does a statistically significant result indicate about experimental data?
- Zero measurement error
- Proven causal link
- Unlikely due to chance
- Perfect correlation
-
Why can a very small effect size still be statistically significant in research?
- Low measurement reliability
- Small sample size
- Large sample size
- High ecological validity
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