Question

ohn ran an experiment and found the "t" value to be significant at the .05 level. In actual fact the null hypothesis is true. What error has John committed and what are his chances of doing so?

Type I error; 1 chance in 20. | ||

Type I error; 1 chance in 100. | ||

Type II error; 1 chance in 20. | ||

Type II error; about 85% chance |

Answer #1

Here, we have found the t statistic to be significant at 5% level of significance, which means that we reject the null hypothesis at that level of significance. But we are given here that in reality the null hypothesis is true. Rejecting a true null hypothesis is called Type I error.

Also the probability of type I error is equal to the level of significance which is 0.05 here that is 1 in 20.

**Therefore Type I error, 1 chance in 20 is the correct
answer here.**

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b. a Type II error.
c. failing to reject the null hypothesis.
d. accepting the null hypothesis when, in fact, it is false.
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researcher.
b. failing to reject the null hypothesis when, in fact, it is
true.
c. incorrectly...

Setting the significance level cutoff at .10 instead of the more
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1 The probability of type II error becomes bigger if the level
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True
False
2
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True
False
3
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False
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If alpha is 0.05 and the p value for your obtained statistic is
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either a Type II error or a Type I error
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