Statistical Significance Flashcards
1
Q
False positive errors
A
When you conclude there is an effect when there isn’t.
2
Q
False negative error
A
When you fail to notice a real effect.
3
Q
Neyman-Pearson system
A
Define a null hypothesis, a hypothesis that there is no effect, and an alternative hypothesis (that there is an effect).
Construct a test that compares the two hypothesis.
Reject the null hypothesis whenever p
4
Q
“p” value
A
Probability value
The probability, under the assumption that there is no true effect or no true difference, of collecting data that shows a difference equal to or more extreme than that what you actually observed.
Measure of surprise, not a measure of size of the effect.
