Educational Psychology / Unit 2 EDP 0125 review, 2 to 3 minutes
What Randomness Licenses
The idea
Two uses of chance decide what a study may claim. Random sampling decides who the findings apply to: when every member of a population had an equal chance of selection, results can be generalized to that population, within a margin of error. Random assignment decides whether cause can be claimed: when chance alone put participants into conditions, known and unknown differences between people are balanced across the groups, so a difference in outcome can be credited to the manipulation. A correlational study cannot claim cause, because a confounding variable may drive both measures. A quasi-experiment looks like an experiment but compares groups that existed beforehand, so a confound can still explain the result. An observational study, however large, cannot show that one habit causes another.
In practice
Worked example: a district reports that students in a new reading program scored higher than students outside it. Ask two questions. Were the schools in the report a random sample of the district's schools? If not, the result may not apply beyond them. Were students assigned to the program at random? If families chose it, motivated families may explain the gain, and the report shows correlation, not cause. A true test would assign classes to the program by chance and compare them on the same measure.
Where people slip
A p-value adds a third question and is often misread. It is the probability of results at least this extreme if chance alone were at work. It is not the probability that the hypothesis is true, nor the probability that chance alone produced the data. So three questions sit behind every claim: significance speaks to chance, sampling to who the results reach, and assignment to cause. A strong study answers all three.
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