Choosing Statistical Tests in AQA A Level Psychology

What statistical test is appropriate when comparing the means of two independent groups?

• Dependent t-test

• Independent t-test

• ANOVA

• Chi-square test

When should you use a chi-squared test in psychological research?

• When analyzing the mean differences between two groups.

• When examining the relationship between a categorical and a continuous variable.

• When determining association between two categorical variables.

• When testing for correlation between two continuous variables.

In what situation would you use a Mann-Whitney U test instead of a t-test?

• When the data is normally distributed

• When the sample sizes are large

• When the data is not normally distributed or when the sample sizes are small.

• When the variances are equal

What is the purpose of conducting a correlation analysis in psychology?

• The purpose of conducting a correlation analysis in psychology is to determine the relationship between two co-variables.

• To identify causation between variables

• To predict future outcomes based on past data

• To determine the statistical significance of a single variable

What is the null hypothesis in a statistical test?

• The mean of the sample

• The alternative hypothesis

• The p-value threshold

• There is no significant difference or relationship between specified populations or variables.

How does the choice of statistical test impact the interpretation of research findings?

• The choice of statistical test impacts the interpretation of research findings by determining the validity and reliability of the conclusions drawn from the data.

• The choice of statistical test only affects the formatting of the research report

• The choice of statistical test has no impact on the interpretation of research findings

• Using a complex statistical test always leads to more accurate conclusions

Why is it important to consider the assumptions of a statistical test before conducting the analysis?

• To make the analysis more complicated

• To waste time

• To confuse the researchers

• To ensure the validity and accuracy of the test results.

What is the importance of calculating effect size in statistical analysis?

• To confuse the readers

• To determine the sample size

• To provide additional information about the magnitude of the relationship

• To increase the complexity of the analysis

How does the level of significance impact the interpretation of statistical results?

• A higher level of significance always indicates a stronger relationship

• A lower level of significance makes the results less reliable

• The level of significance determines the threshold for rejecting the null hypothesis

• The level of significance has no impact on the analysis