Question

Consider a hypothesis test of the claim that wearing a particular type of shoe reduces the likelihood of developing a bunion. Identify the Type I and Type II errors for this test.

A. A Type I error occurs when the difference between the sample proportion and the hypothesized proportion is statistically significant, but the test fails to detect it. A Type II error is when the difference between the sample proportion and the hypothesized proportion is not statistically significant, but the test concludes that it is.
B. A Type I error occurs when the difference between the sample proportion and the hypothesized proportion is not statistically significant, but the test concludes that it is. A Type II error is when the difference between the sample proportion and the hypothesized proportion is statistically significant, but the test fails to detect it.
C. A Type I error is concluding that wearing a particular type of shoe effectively reduces the likelihood of developing a bunion, when in reality there is not enough evidence to support that conclusion. A Type II error is concluding that wearing a particular type of shoe has no effect on the likelihood of developing a hunion when in reality there ie anonoh arridence to an art that conclusion aboutos career Deivacy policy terms of use | contact us field MacBook Air
D. A Type I error occurs when the difference between the sample proportion and the hypothesized proportion is not statistically significant, but the test concludes that it is A Type II error is when the difference between the sample proportion and the hypothesized proportion is statistically significant, but the test fails to detect it.
E. A Type I error is concluding that wearing a particular type of shoe effectively reduces the likelihood of developing a bunion, when in reality there is not enough evidence to support that conclusion. A Type II error is concluding that wearing a particular type of shoe has no effect on the likelihood of developing a bunion, when in reality there is enough evidence to support that conclusion The Type I and Type II errors cannot be determined from the given information.
F. A Type I error is concluding that wearing a particular type of shoe has no effect on the likelihood of developing a bunion, when in reality there is enough evidence to support that conclusion. A Type II error is concluding that wearing a particular type of shoe effectively reduces the likelihood of developing a bunion, when in reality there is not enough evidence to support that conclusion about us career privacy policy terms of use contact us he MacBook Air

Answer 1

The Type I and Type II errors for this test B. A Type I error occurs when the difference between the sample proportion and the hypothesized proportion is not statistically significant, but the test concludes that it is. A Type II error is when the difference between the sample proportion and the hypothesized proportion is statistically significant, but the test fails to detect it is correct .

In hypothesis testing, Type I and Type II errors are defined as follows:

Type I Error (False Positive): This occurs when the null hypothesis is true, but the test incorrectly rejects it.

In the context of the given scenario, a Type I error would be concluding that wearing a particular type of shoe reduces the likelihood of developing a bunion when, in reality, there is no such effect.

Type II Error (False Negative): This occurs when the null hypothesis is false, but the test fails to reject it.

In the context of the given scenario, a Type II error would be failing to conclude that wearing a particular type of shoe reduces the likelihood of developing a bunion when, in reality, there is a significant effect.

So, option B correctly states that a Type I error occurs when the difference between the sample proportion and the hypothesized proportion is not statistically significant, but the test concludes that it is.

A Type II error is when the difference between the sample proportion and the hypothesized proportion is statistically significant, but the test fails to detect it.