Statistical significance means there is a cause and effect relationship between two things. Even though the difference in score was small, the math gives us reason to believe that difference is not random.
The reason for this is that the variance in score within each sample is much less than the difference in average score between the samples.
For example, let’s say you have 2 classes of students, class A and class B. Both classes take a test. Class A gets an average score of 80, and class B gets an average score of 75.
Now consider two more scenarios.
1. The scores of class A were: 75, 80, 85. The scores of class B were: 65, 75, 85.
2. The scores of class A were: 80, 80, 80. The scores of class B were: 75, 75, 75.
There’s nothing shocking about scenario 1. You could easily assume these students are randomly distributed according to intellect and knowledge. But look at at scenario 2. Something’s off. For every student in class A to score exactly 5 points higher, we have to believe there’s a reason: perhaps those students are smarter or perhaps their teacher covered the curriculum better.
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