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Type I and Type II Errors. In Exercises 29鈥32, provide statements that identify the type I error and the type II error that correspond to the given claim. (Although conclusions are usually expressed in verbal form, the answers here can be expressed with statements that include symbolic expressions such as p = 0.1.).

The proportion of people who require no vision correction is less than 0.25.

Short Answer

Expert verified

A type I error occurs when the actual value of the proportion is equal to 0.25, and the researcher rejects the claim\(p = 0.25\)and supports the claim\(p < 0.25\).

A type II error occurs when the actual value of the proportion is less than 0.25, and the researcher fails to reject the claim \(p = 0.25\).

Step by step solution

01

Given information

It is claimed that the proportion of people who require no vision correction is less than 0.25.

02

Hypotheses

Let p be the population proportion of people who require no vision correction.

According to the stated claim, the following hypotheses are set up:

Null hypothesis \({H_0}:p = 0.25\).

Alternative hypothesis \({H_A}:p < 0.25\).

03

Types of errors

The two types of errors made while conducting hypotheses tests are defined below.

Type I error: Rejecting the null hypothesis when the null hypothesis is true is a type I error and is denoted by\(\alpha \).

Type II error: Failing to reject the null hypothesis when the null hypothesis is false is a type II error and is denoted by\(\beta \).

In accordance with the given claim, the following statements define the type I error and the type II error:

Type I error: When the actual value of the proportion is equal to 0.25, and the researcher rejects the claim \(p = 0.25\) and supports the claim \(p < 0.25\), a type I error is made.

Type II error: When the actual value of the proportion is less than 0.25, and the researcher fails to reject the claim \(p = 0.25\), a type II error is made.

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Most popular questions from this chapter

Calculating Power Consider a hypothesis test of the claim that the Ericsson method of gender selection is effective in increasing the likelihood of having a baby girl, so that the claim is p>0.5. Assume that a significance level of = 0.05 is used, and the sample is a simple random sample of size n = 64.

a. Assuming that the true population proportion is 0.65, find the power of the test, which is the probability of rejecting the null hypothesis when it is false. (Hint: With a 0.05 significance level, the critical value is z = 1.645, so any test statistic in the right tail of the accompanying top graph is in the rejection region where the claim is supported. Find the sample proportion in the top graph, and use it to find the power shown in the bottom graph.)

b. Explain why the green-shaded region of the bottom graph represents the power of the test.

Technology. In Exercises 9鈥12, test the given claim by using the display provided from technology. Use a 0.05 significance level. Identify the null and alternative hypotheses, test statistic, P-value (or range of P-values), or critical value(s), and state the final conclusion that addresses the original claim.

Airport Data Speeds Data Set 32 鈥淎irport Data Speeds鈥 in Appendix B includes Sprint data speeds (mbps). The accompanying TI-83/84 Plus display results from using those data to test the claim that they are from a population having a mean less than 4.00 Mbps. Conduct the hypothesis test using these results.

Testing Claims About Proportions. In Exercises 9鈥32, test the given claim. Identify the null hypothesis, alternative hypothesis, test statistic, P-value, or critical value(s), then state the conclusion about the null hypothesis, as well as the final conclusion that addresses the original claim. Use the P-value method unless your instructor specifies otherwise. Use the normal distribution as an approximation to the binomial distribution, as described in Part 1 of this section.

Overtime Rule in Football Before the overtime rule in the National Football League was changed in 2011, among 460 overtime games, 252 were won by the team that won the coin toss at the beginning of overtime. Using a 0.05 significance level, test the claim that the coin toss is fair in the sense that neither team has an advantage by winning it. Does the coin toss appear to be fair?

Technology. In Exercises 9鈥12, test the given claim by using the display provided from technology. Use a 0.05 significance level. Identify the null and alternative hypotheses, test statistic, P-value (or range of P-values), or critical value(s), and state the final conclusion that addresses the original claim.

Old Faithful Data Set 23 鈥淥ld Faithful鈥 in Appendix B includes data from 250 random eruptions of the Old Faithful geyser. The National Park Service makes predictions of times to the next eruption, and the data set includes the errors (minutes) in those predictions. The accompanying Statdisk display results from using the prediction errors (minutes) to test the claim that the mean prediction error is equal to zero. Comment on the accuracy of the predictions.

Final Conclusions. In Exercises 25鈥28, use a significance level of = 0.05 and use the given information for the following:

a. State a conclusion about the null hypothesis. (Reject H0 or fail to reject H0.)

b. Without using technical terms or symbols, state a final conclusion that addresses the original claim.

Original claim: Fewer than 90% of adults have a cell phone. The hypothesis test results in a P-value of 0.0003.

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