Hypothesis Testing, Errors & Power Practice

• The hypothesis that there is a significant effect or difference.

• The hypothesis that there is no effect or difference.

• The hypothesis that the sample mean is greater than the population mean.

• The hypothesis that the sample mean is less than the population mean.

• The hypothesis that there is no effect or difference.

• The hypothesis that there is a significant effect or difference.

• The hypothesis that the sample mean is equal to the population mean.

• The hypothesis that the sample mean is less than the population mean.

What is a Type I error in hypothesis testing?

• Failing to reject the null hypothesis when it is false.

• Rejecting the null hypothesis when it is true.

• Accepting the alternative hypothesis when it is false.

• Accepting the null hypothesis when it is true.

What is a Type II error in hypothesis testing?

• Rejecting the null hypothesis when it is true.

• Failing to reject the null hypothesis when it is false.

• Accepting the null hypothesis when it is true.

• Accepting the alternative hypothesis when it is true.

What does the power of a statistical test refer to?

• The probability of rejecting the null hypothesis when it is true.

• The probability of rejecting the null hypothesis when it is false.

• The probability of accepting the null hypothesis when it is true.

• The probability of accepting the null hypothesis when it is false.

Which of the following increases the power of a test?

• Decreasing the sample size.

• Decreasing the effect size.

• Increasing the probability of a Type II error.

• 0.95

• 0.05

• 0.10

• 0.50

Which of the following is true about the relationship between Type I and Type II errors?

• Increasing the probability of a Type I error decreases the probability of a Type II error.

• Increasing the probability of a Type I error increases the probability of a Type II error.

• Type I and Type II errors are independent of each other.

• Type I and Type II errors are the same.

In hypothesis testing, what does a p-value represent?

• The probability of observing the sample data given that the null hypothesis is true.

• The probability of observing the sample data given that the alternative hypothesis is true.

• The probability of the null hypothesis being true.

• The probability of the alternative hypothesis being true.

Which of the following is a method to reduce Type II errors?

• Decrease the sample size.

• Increase the sample size.