Dependent Samples Tests

The Wilcoxon test is more robust against outliers and heavy-tailed distributions compared to:

• Independent samples t-test

• Paired samples t-test

• Mann-Whitney U test

• Kruskal-Wallis test

In a Wilcoxon test, what does a p-value less than 0.05 indicate?

• The null hypothesis is not rejected.

• The data are normally distributed.

• The null hypothesis is rejected.

• The test is inconclusive.

The Wilcoxon test examines:

• Differences in means.

• Differences in medians.

• Differences in proportions.

• Differences in variances.

Which test for dependent samples is appropriate when working with ordinal data?

• Independent samples t-test

• Paired samples t-test

• Wilcoxon signed-rank test

• Mann-Whitney U test

What is the primary assumption for conducting a dependent samples t-test?

• Data must be on an ordinal scale.

• Each pair of samples must be independent.

• Population variance should be known.

• Samples must come from data with a normal distribution

The dependent samples t-test is used when:

• Two different groups are being compared.

• The same participants are measured under two conditions.

• Three or more groups are measured on the same dependent variable.

• The data is non-numeric.

When interpreting the t-value from a dependent samples t-test, a very large t-value typically indicates that:

• There is no significant difference between the groups.

• There is a significant difference between the groups.

• The sample size is too small to determine significance.

• Variance between groups is identical.

What does a p-value less than 0.05 imply in the analysis of a paired samples t-test?

• Most data points fall outside the normal range of variability.

• The effect observed in the paired samples is minimal or nonexistent.

• There is a significant statistical difference between the paired samples.

• The data confirms the assumptions of the null hypothesis.

Which of the following is true about the Wilcoxon signed-rank test?

• It requires data to be at least on an ordinal scale.

• It can only be used for independent samples.

• It assumes data are normally distributed.

• It compares means rather than medians.

The Wilcoxon signed-rank test is particularly useful when:

• The sample size is very large.

• Data do not meet the assumption of normality.

• Comparing more than two dependent samples.

• The data are not in ordinal scale