DSRT 734: Comparing Grades From Different Students Across Two Years

DSRT 734 Question

A teacher has changed their teaching style for this year and wants to
test if their students grades are significantly different this year
compared to their student's grades last year. The students are different
people. Assuming the grades are symmetrically distributed and scored
between a 0% and a 100%, what is the correct test for the teacher to run?

Option A

Independent samples t-test


Option B

Pearson's correlation


Option C

Paired samples t-test


Option D

Mann-Whitney U test

What this question assesses

This item assesses whether the explicit statement that students differ across years is used to identify sample independence, and how outcome distribution information bears on parametric versus rank-based comparison choices.

How to approach this type of question

Describe the sampling units first: last year’s students and this year’s students are different people, so there is no natural student-by-student pairing. Grades are quantitative values bounded between zero and one hundred. Record what “symmetrically distributed” says, but also recognize that real analysis would inspect group shapes, unusual values, sample sizes, and variance behavior. Compare each candidate’s purpose: some assess association between paired variables, some require repeated or matched observations, and the independent-sample alternatives make different distributional interpretations. The teaching-style change supplies context but does not by itself establish causality because the yearly groups and other conditions may differ. Use independence, scale, and assumptions to evaluate the options, then phrase any eventual conclusion as a comparison supported by the sampled data. The final method choice is intentionally omitted.

When documenting the choice, state explicitly that different students make the samples independent even though both groups belong to the same course across years. Consider whether grade bounds create ceiling effects and whether symmetry was evaluated separately in each group. If a robust or rank-based method is selected, explain the assumption evidence rather than using it automatically. Any observed difference may coexist with cohort changes, so the teaching style cannot be isolated without a stronger design.

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