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Set up hypothesis tests with null and alternative hypotheses, significance level, and p-values.
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Avoid these 3 frequent errors
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Null Hypothesis (): The "no effect" or "no difference" claim. Always includes .
Alternative Hypothesis (): What we're trying to find evidence for.
Types of alternative hypotheses:
The significance level is the threshold for deciding when to reject .
Common values: (most common), ,
The test statistic measures how far the sample result is from what predicts:
The p-value is the probability of obtaining a test statistic as extreme as (or more extreme than) the observed value, assuming is true.
Never say "accept " — we only fail to reject it.
A result is statistically significant at level if the p-value .
Statistical significance ≠ practical significance. A very large sample can detect tiny, meaningless differences.
AP Tip: Always state your conclusion in context: "Since the p-value of 0.03 is less than , we reject . There is convincing evidence that [context about ]."