Significance Tests
Definition
Significance tests help determine whether an observed effect or difference between groups is statistically significant or simply due to chance variation.
Analogy
Imagine you and your friend are playing a game, and you win 10 times in a row. A significance test would help determine if your winning streak is due to skill or just random luck.
Related terms
Null Hypothesis: The null hypothesis states that there is no significant difference or effect between groups, and any observed differences are due to chance.
Type I Error: A type I error occurs when we reject the null hypothesis when it is actually true, leading us to believe there is an effect or difference when there isn't.
P-value: The p-value represents the probability of obtaining results as extreme as the observed data, assuming the null hypothesis is true. A smaller p-value suggests stronger evidence against the null hypothesis.
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