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- Each test is about one proportion p with null value p_0.H_a\colon p > p_0,\ z = 1.28H_a\colon p < p_0,\ z = -2.61H_a\colon p \neq p_0,\ z = 1.96H_a\colon p \neq p_0,\ z = -0.47H_a\colon p < p_0,\ z = 1.12
- Do not compute anything.H_a\colon p > 0.40,\ \hat{p} = 0.37H_a\colon p < 0.65,\ \hat{p} = 0.58H_a\colon p \neq 0.10,\ \hat{p} = 0.13H_a\colon p \neq 0.72,\ \hat{p} = 0.66H_a\colon p < 0.25,\ \hat{p} = 0.31
- A made-up plumbing company has found over many years that 15% of its repair calls need a second visit, usually because the van was missing a part.
- A made-up hawk-watch station has found over many years that 38% of the red-tailed hawks it bands each autumn are juveniles (in their first year).
- A made-up beachcombing club says that 10% of the sea glass on its beach is blue.
- A made-up trading card company says that 20% of its packs contain a holographic card.
- A made-up pretzel factory has found that 20% of its bags hold five or more broken pretzels.
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p-values and the significance level: the lesson ›More Chapter 8 worksheets: Inference for proportions: significance tests
- 8.1Comparing two treatments by re-randomizing
- 8.2Null and alternative hypotheses
- 8.3Test statistic
- 8.4p-values and the significance level
- 8.5Deciding and concluding from a p-value
- 8.6One sample test for a proportion
- 8.7Test for a difference of proportions
- 8.8Type I and Type II errors
- 8.9Power and what raises it
- 8.10Cautions about significance