Chapter Nine
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10 Terms
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type I error
occurs if a test rejects the null when the null is true. that is, the test finds convincing evidence that the alternative hypothesis is true when it really isn’t
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type II error
occurs if a test fails to reject the null when the null is true. that is, the test does not find convincing evidence that the alternative hypothesis is true when it is
3
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as sample size increases
test power: increases
type I: stays the same
type II: decreases
type I: stays the same
type II: decreases
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probability of a type I error
the significance level is the probability of a type I error
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probability of a type II error
a type II error is inversely related to the probability of a type I error
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conclusion
because our p-value is 0.637 > a = 0.05, we fail to reject the null. there is not convincing evidence that the true proportion of \[context\] differs from 25%
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when the p-value is less than the significance value
we reject the null
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when the p-value is more than the significance value
we fail to reject the null
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as significance level increases
test power: increases
type I: increases
type II: decreases
type I: increases
type II: decreases
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as the null and true value get farther apart
test power: increases
type I: stays the same
type II: decreases
type I: stays the same
type II: decreases