Lesson 8.2.2
8.2.2 Cross-cultural research and data analysis in health psychology Quiz: Pearson Edexcel Psychology, Unit 8
20 questions
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Lesson 8.2.2, Cross-cultural research and data analysis in health psychology: 20 multiple choice questions for the Pearson Edexcel Psychology (9PS0), Unit 8: Health psychology, written with Revision Ninja.
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The 20 questions
-
What is a major advantage of cross-cultural research on drug use for the nature-nurture debate?
- It shows that all cultures have identical drinking habits
- It removes the need for any statistical test
- It proves that nurture has no role in any behaviour
- Consistent patterns across cultures suggest a biological basis, while differences suggest environmental influence
-
A cross-cultural study finds that alcohol use differs widely between two countries with similar genetic make-up. Which conclusion is best supported?
- The study has proved that culture has no effect
- Genes alone must explain the difference
- Environmental and cultural factors are likely to contribute to differences in alcohol use
- Alcohol use cannot differ between countries
-
Why is it difficult to make valid comparisons in cross-cultural health research?
- Measures and questions may have different meanings or translations in different cultures
- Cultural comparisons always produce identical data
- Cross-cultural research only uses animals
- Health behaviours never vary between cultures
-
A researcher reports the median number of drinks per week in a sample of 40 students. Which measure of central tendency is this?
- The standard deviation
- The range
- The critical value
- The median
-
Weekly alcohol units for five people are 2, 4, 4, 6, 14. Which is the best measure of the typical value given the extreme score of 14?
- The mean of 6
- The median of 4
- The mode of 14
- The range of 12
-
Using the same five weekly unit values of 2, 4, 4, 6 and 14, what is the range?
- 14
- 12
- 4
- 8
-
A researcher wants to test whether the number of cigarettes smoked per day is related to the age of smokers, using ordinal data. Which test should be used?
- Spearman's rho
- Mann-Whitney U
- Wilcoxon signed-ranks
- Chi-squared test of independence on counts of cigarettes
-
A researcher compares smoking frequency between two independent groups of adults who received different treatments. The data are ordinal. Which test is appropriate?
- Wilcoxon signed-ranks
- Pearson's correlation
- Mann-Whitney U
- Spearman's rho
-
A researcher measures drinking before and after a campaign in the same participants. Which test is most appropriate for ordinal data?
- Spearman's rho
- Mann-Whitney U test
- Chi-squared test
- Wilcoxon signed-ranks test
-
A chi-squared test on a 2x2 table gives an observed value of 5.2. The critical value at p≤.05 with 1 degree of freedom is 3.84. What is the conclusion?
- The result is not significant because the observed value is below the critical value
- The test is invalid because 5.2 is a whole number
- Reject the null hypothesis, because the observed value exceeds the critical value
- Accept the null hypothesis, because the observed value is larger than the critical value
-
A researcher's Spearman's rho is 0.25 with a critical value of 0.38 at p≤.05 for the sample size. Which conclusion is correct?
- The sample must be too large to test
- The result is significant, so the null hypothesis is rejected
- The result is not significant, so the null hypothesis is retained
- The correlation is perfect
-
Which statement about levels of significance is most accurate?
- A p value of .05 means the hypothesis is 95 per cent proven
- A p value of .05 means the study has no errors
- A p value of .05 means the sample was 5 per cent of the population
- A p value of .05 means there is a 5 per cent probability of obtaining the result if the null hypothesis is true
-
A researcher rejects the null hypothesis when it is actually true. Which type of error has been made?
- Sampling error only
- Type I error
- Type II error
- Ecological error
-
A researcher retains the null hypothesis when a real effect exists. Which error is this?
- Demand characteristic
- Type II error
- Type I error
- Operationalisation error
-
Why would a researcher set a stricter significance level, such as p≤.01, rather than p≤.05?
- To make it easier to find significant results
- To reduce the risk of a Type I error
- To remove the need for a critical value
- To increase the risk of a Type I error
-
A cross-cultural survey finds that men report more alcohol use than women in every country sampled. Which conclusion is most appropriate?
- The results prove that biology is the only cause
- Women cannot drink alcohol in any country
- There is a consistent gender difference in self-reported drinking across these samples, although causes need further study
- Gender causes alcohol use in every society
-
A researcher calculates the mean alcohol consumption for a sample and finds it is 12 units per week with a standard deviation of 3. Which statement is correct?
- Most scores lie within about 3 units of the mean
- The median must be 3 units
- All scores lie between 9 and 15 units
- The sample is representative of the entire world
-
A researcher's data are ordinal and not normally distributed, so they choose a non-parametric test. What does this decision reflect?
- A choice to remove all outliers from the data
- Awareness of the level of measurement and distribution of the data when choosing a test
- A requirement that the sample must be larger than 1000
- A mistake, because non-parametric tests can never be used
-
A researcher finds a positive Spearman's rho between the age at which people first drink alcohol and their later alcohol use. Which conclusion is correct?
- The result shows that age has no effect on drinking
- There is no relationship between the two variables
- Earlier drinking is associated with higher later use, but this does not prove that early drinking causes later use
- Early drinking causes later use with certainty
-
A researcher uses thematic analysis on interviews about drinking cultures across three countries. Which step is central to the method?
- Measuring the range of the interview lengths
- Calculating a mean for each interview
- Identifying patterns of meaning across the data and grouping them into themes
- Testing a directional hypothesis with a chi-squared test
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