Health Research Methods Quiz

What is the purpose of comparative statistics?

• To test for sameness

• To test for difference

• To compare means and proportions

• To compare before-and-after characteristics

What is the null hypothesis in statistical tests?

• There is a difference between the values being compared

• There is no difference between the values being compared

• The test result is statistically significant

• The test result is not statistically significant

What does a small p value indicate?

• The observed test result is highly likely to have occurred by chance

• The observed test result is highly unlikely to have occurred by chance

• The null hypothesis is rejected

• The null hypothesis is not rejected

What is the significance level commonly used in statistical tests?

• 0.01

• 0.05

• 0.10

• 0.50

When is a one-sided p-value used in statistical tests?

• When a direction is specified in the alternative hypothesis

• When a direction is not specified in the alternative hypothesis

• When comparing means of two sets of data

• When comparing the proportion of a binomial variable

What must researchers confirm before running a statistical test?

• The variables meet the assumptions of the test

• The variables have a normal distribution

• The variables are independent

• The variables have equal variances

Which statistical test compares the means of two sets of data?

• Binomial test

• Chi-square goodness-of-fit test

• ANOVA

• Correlation analysis

What does qualitative analysis aim to understand?

• The distribution of variables in a population

• The statistical significance of results

• The ways people find meaning in their experiences

• The relationship between two variables

What is inter-rater reliability in qualitative analysis?

• The consistency of multiple coders in coding the data

• The accuracy of data interpretation

• The applicability of qualitative data in other circumstances

• The consistency of data collection, analysis, and interpretation methods

What is confirmability in qualitative analysis?

• The accuracy of data interpretation

• The consistency of data collection, analysis, and interpretation methods

• The neutrality of the study results

• The absence of researcher bias