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One type of error in a hypothesis test is rejecting the null hypothesis when it is true. What is the other type of error that might occur when a hypothesis test is carried out?

Short Answer

Expert verified
The other type of error that might occur when a hypothesis test is carried out is a Type II error. This is when we fail to reject the null hypothesis when it is actually false (a false negative).

Step by step solution

01

Understanding Type II error

Type II error, in the context of hypothesis testing, is the error that occurs when the null hypothesis is not rejected when it actually should be rejected. This is also known as a false negative. In other words, the second type of error occurs when failing to detect a difference or effect that is actually present.
02

Type II Error Definition

Therefore, the other type of error that might occur when a hypothesis test is carried out is when we fail to reject the null hypothesis when it is false. This error is known as a Type II error or a false negative.

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Most popular questions from this chapter

In a survey conducted by Yahoo Small Business, 1,432 of 1,813 adults surveyed said that they would alter their shopping habits if gas prices remain high (Associated Press, November 30,2005\() .\) The article did not say how the sample was selected, but for purposes of this exercise, assume that the sample is representative of adult Americans. Based on the survey data, is it reasonable to conclude that more than threequarters of adult Americans would alter their shopping habits if gas prices remain high?

A county commissioner must vote on a resolution that would commit substantial resources to the construction of a sewer in an outlying residential area. Her fiscal decisions have been criticized in the past, so she decides to take a survey of residents in her district to find out if they favor spending money for a sewer system. She will vote to appropriate funds only if she can be reasonably sure that a majority of the people in her district favor the measure. What hypotheses should she test?

The article "Most Customers OK with New Bulbs" (USA Today, Feb. 18,2011 ) describes a survey of 1,016 randomly selected adult Americans. Each person in the sample was asked if they have replaced standard light bulbs in their home with the more energy efficient compact fluorescent (CFL) bulbs. Suppose you want to use the survey data to determine if there is evidence that more than \(70 \%\) of adult Americans have replaced standard bulbs with CFL bulbs. Let \(p\) denote the proportion of all adult Americans who have replaced standard bulbs with CFL bulbs. a. Describe the shape, center, and spread of the sampling distribution of \(\hat{p}\) for random samples of size 1,016 if the null hypothesis \(H_{0}: p=0.70\) is true. b. Would you be surprised to observe a sample proportion as large as \(\hat{p}=0.72\) for a sample of size 1,016 if the null hypothesis \(H_{0}: p=0.70\) were true? Explain why or why not. c. Would you be surprised to observe a sample proportion as large as \(\hat{p}=0.75\) for a sample of size 1,016 if the null hypothesis \(H_{0}: p=0.70\) were true? Explain why or why not. d. The actual sample proportion observed in the study was \(\hat{p}=0.71\). Based on this sample proportion, is there convincing evidence that more than \(70 \%\) have replaced standard bulbs with CFL bulbs, or is this sample proportion consistent with what you would expect to see when the null hypothesis is true? Support your answer with a probability calculation.

One type of error in a hypothesis test is failing to reject a false null hypothesis. What is the other type of error that might occur when a hypothesis test is carried out?

Explain why a \(P\) -value of 0.0002 would be interpreted as strong evidence against the null hypothesis.

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