ACT (Enhanced)ReadingHard
In a research paper, an author cites a study from 1995 that used a small sample size and a non-random selection method. The author then uses the findings of this study as foundational support for a contemporary argument about public opinion trends. What is the most significant weakness in the author's use of this evidence?
- AThe study's findings are too old to be relevant to current trends.
- BThe research paper likely lacks original data collection, relying solely on secondary sources.
- CThe small sample size and non-random selection limit the generalizability of the findings.
- DThe author should have cited multiple older studies for better historical context.
Show answer & explanationAnswer & explanation
Correct answer: C. The small sample size and non-random selection limit the generalizability of the findings.
A small sample size and non-random selection are critical methodological flaws that severely limit the extent to which a study's results can be applied to a larger population or different contexts. This directly undermines the 'generalizability' of the findings, making them unsuitable as 'foundational support' for broad claims about public opinion trends.
Why the other options are wrong
- A. While age can be a factor, the more fundamental weakness lies in the *methodology* itself, regardless of age. A well-designed 1995 study might still be relevant for historical comparison, but this one has inherent flaws.
- B. Relying on secondary sources isn't inherently a weakness if those sources are robust. The weakness here is the *quality* of the specific secondary source chosen, not just that it's a secondary source.
- D. Citing multiple older studies wouldn't fix the fundamental methodological flaws of this specific study, nor is it the *most significant* weakness identified.
Evaluating Evidence: Generalizability
The extent to which the findings of a study can be applied or extended to a larger population or different contexts.
- Influenced by sample size and selection method.
- Random sampling enhances generalizability.
- Small or biased samples limit applicability.
Memory trick: Evidence's might: sample's right, generalization's light.