Statistics Quiz

A Type I error occurs when the null hypothesis is true and is rejected (false positive). What is the probability of a Type I error?

• P(Type I error)

• P(Type II error)

• P(power)

• 1 - P(power)

A Type II error occurs when the alternative hypothesis is true and the null hypothesis is not rejected (false negative). What is the probability of a Type II error?

• P(Type I error)

• P(Type II error)

• P(power)

• 1 - P(power)

Did the researchers randomly assign the subjects to treatment groups?

• YES

• NO

Tags

CCSS.HSS.IC.B.3

True or False:

The larger your confidence interval is, the more sure (higher confidence level) you can be.

• True

• False

Tags

CCSS.HSS.IC.B.4

Define a Type I error?

• The failure to reject a false null hypothesis
• Rejecting a true null hypothesis
• The acceptance to reject a null hypothesis
• Accepting a true null  hypothesis

What is a Type I error in hypothesis testing?

• Accepting the null hypothesis when it is false

• Rejecting the null hypothesis when it is true

• Accepting the alternative hypothesis when it is false

• Rejecting the alternative hypothesis when it is true

What is the main goal of hypothesis testing?

• To determine the sample size

• To estimate the population parameters

• To make inferences about the population based on sample data

• To calculate the mean of the population

Tags

CCSS.HSS.IC.B.3

Which of the following best describes when a researcher would commit a Type I error?

• When the researcher fails to detect an effect that is present

• When the researcher detects an effect that is not actually present

• When the researcher correctly identifies that there is no effect

• When the researcher correctly identifies that there is an effect

How can the risk of committing a Type I error be reduced?

• Increase the significance level (alpha)

• Decrease the significance level (alpha)

• Increase the sample size

• Decrease the sample size

What role does the significance level (alpha) play in hypothesis testing?

• It determines the sample size needed for the test.

• It is the boundary used to determine if an observed result is unlikely to happen by chance alone.

• It is the probability of getting evidence for the alternative hypothesis as strong or stronger that the observed evidence by chance alone.

• It measures the central tendency of the data.

Tags

CCSS.HSS.IC.B.4