Chapter Nine

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type I error

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10 Terms

1

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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2

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

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3

as sample size increases

test power: increases

type I: stays the same

type II: decreases

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4

probability of a type I error

the significance level is the probability of a type I error

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5

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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6

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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7

when the p-value is less than the significance value

we reject the null

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8

when the p-value is more than the significance value

we fail to reject the null

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9

as significance level increases

test power: increases

type I: increases

type II: decreases

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10

as the null and true value get farther apart

test power: increases

type I: stays the same

type II: decreases

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