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Based on the case context, explain what expectation the research team should have formed regarding the statistical significance of their findings before running the program, and what they should diagnose or decide upon receiving the non-significant software output.
Case context: A research team is investigating the effect of a new study technique on exam scores. After gathering data from a medium-sized sample, they calculate the descriptive statistics and find a very strong relationship between the technique and test scores. However, when they run their statistical analysis program, the output indicates that the result is not statistically significant.
Question: Based on the case context, explain what expectation the research team should have formed regarding the statistical significance of their findings before running the program, and what they should diagnose or decide upon receiving the non-significant software output.
Sample answer: According to the general heuristic, the research team should have expected a strong relationship in a medium-sized sample to be reliably statistically significant. When the software output contradicts this expectation by reporting a non-significant result, the team should recognize this mismatch. They should decide to check their analyses for potential computational or interpretive errors, as the intuitive judgment serves as an essential safeguard for detecting such issues.
Key points:
- Expect statistical significance for strong relationships in medium samples.
- Identify the conflict between the expectation and the software output.
- Diagnose the mismatch as a potential computational or interpretive error.
- Use intuitive judgment as a safeguard to double-check the analysis.
Rubric: The answer must explain that a strong relationship in a medium-sized sample is expected to be statistically significant, recognize the conflict with the software output, and justify checking the data/analyses for computational or interpretive errors.
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Research Methods in Psychology - 4th American Edition @ KPU
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