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According to areport on consumer fraud and identity theft, 22% of all complaints during one year were for identity theft. In that year, Michigan had 322 complaints of identity theft out of 1457 consumer complaints. Does this data provide enough evidence to show that Michigan had a lower proportion of identity theft than 22%? State the Type I and Type II errors in this case. State the Type I error. O Concluding that the proportion of complaints from identity theft in Michigan is 22%, when it is less than 22%. O Concluding that the proportion of complaints from identity theft in Michigan is 22%, when it is higher than 22%. O Concluding that the proportion of complaints from identity theft in Michigan is less than 22%, when it is 22%. Concluding that the proportion of complaints from identity theft in Michigan is higher than 22%, when it is 22%. State the Type II error. O Concluding that the proportion of complaints from identity theft in Michigan is 22%, when it is higher than 22%. O Concluding that the proportion of complaints from identity theft in Michigan is 22%, when it is less than 22%. Concluding that the proportion of complaints from identity theft in Michigan is less than 22%, when it is 22%. Concluding that the proportion of complaints from identity theft in Michigan is higher than 22%, when it is 22%.

According to areport on consumer fraud and identity theft, 22% of all complaints during one year were for identity theft. In that year, Michigan had 322 complaints of identity theft out of 1457 consumer complaints. Does this data provide enough evidence to show that Michigan had a lower proportion of identity theft than 22%? State the Type I and Type II errors in this case. State the Type I error. O Concluding that the proportion of complaints from identity theft in Michigan is 22%, when it is less than 22%. O Concluding that the proportion of complaints from identity theft in Michigan is 22%, when it is higher than 22%. O Concluding that the proportion of complaints from identity theft in Michigan is less than 22%, when it is 22%. Concluding that the proportion of complaints from identity theft in Michigan is higher than 22%, when it is 22%. State the Type II error. O Concluding that the proportion of complaints from identity theft in Michigan is 22%, when it is higher than 22%. O Concluding that the proportion of complaints from identity theft in Michigan is 22%, when it is less than 22%. Concluding that the proportion of complaints from identity theft in Michigan is less than 22%, when it is 22%. Concluding that the proportion of complaints from identity theft in Michigan is higher than 22%, when it is 22%.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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**Educational Content on Type I and Type II Errors** **Introduction:** According to a report on consumer fraud and identity theft, 22% of all complaints during one year were for identity theft. In that year, Michigan had 322 complaints of identity theft out of 1,457 consumer complaints. Based on this data, is there enough evidence to show that Michigan had a lower proportion of identity theft than 22%? We will explore the concepts of Type I and Type II errors in this context. **Type I Error:** A Type I error occurs when we incorrectly reject a true null hypothesis. In this scenario, the null hypothesis is that the proportion of identity theft complaints in Michigan is 22%. Options for Type I error: - Concluding that the proportion of complaints from identity theft in Michigan is 22%, when it is less than 22%. - Concluding that the proportion of complaints from identity theft in Michigan is 22%, when it is higher than 22%. - Concluding that the proportion of complaints from identity theft in Michigan is less than 22%, when it is 22%. - Concluding that the proportion of complaints from identity theft in Michigan is higher than 22%, when it is 22%. **Type II Error:** A Type II error occurs when we fail to reject a false null hypothesis. Here, the null hypothesis claims the proportion of identity theft complaints is 22%, when it differs. Options for Type II error: - Concluding that the proportion of complaints from identity theft in Michigan is 22%, when it is higher than 22%. - Concluding that the proportion of complaints from identity theft in Michigan is 22%, when it is less than 22%. - Concluding that the proportion of complaints from identity theft in Michigan is less than 22%, when it is 22%. - Concluding that the proportion of complaints from identity theft in Michigan is higher than 22%, when it is 22%. **Conclusion:** Understanding Type I and Type II errors is crucial in hypothesis testing, helping us carefully interpret data and avoid making incorrect conclusions.
Transcribed Image Text:**Educational Content on Type I and Type II Errors** **Introduction:** According to a report on consumer fraud and identity theft, 22% of all complaints during one year were for identity theft. In that year, Michigan had 322 complaints of identity theft out of 1,457 consumer complaints. Based on this data, is there enough evidence to show that Michigan had a lower proportion of identity theft than 22%? We will explore the concepts of Type I and Type II errors in this context. **Type I Error:** A Type I error occurs when we incorrectly reject a true null hypothesis. In this scenario, the null hypothesis is that the proportion of identity theft complaints in Michigan is 22%. Options for Type I error: - Concluding that the proportion of complaints from identity theft in Michigan is 22%, when it is less than 22%. - Concluding that the proportion of complaints from identity theft in Michigan is 22%, when it is higher than 22%. - Concluding that the proportion of complaints from identity theft in Michigan is less than 22%, when it is 22%. - Concluding that the proportion of complaints from identity theft in Michigan is higher than 22%, when it is 22%. **Type II Error:** A Type II error occurs when we fail to reject a false null hypothesis. Here, the null hypothesis claims the proportion of identity theft complaints is 22%, when it differs. Options for Type II error: - Concluding that the proportion of complaints from identity theft in Michigan is 22%, when it is higher than 22%. - Concluding that the proportion of complaints from identity theft in Michigan is 22%, when it is less than 22%. - Concluding that the proportion of complaints from identity theft in Michigan is less than 22%, when it is 22%. - Concluding that the proportion of complaints from identity theft in Michigan is higher than 22%, when it is 22%. **Conclusion:** Understanding Type I and Type II errors is crucial in hypothesis testing, helping us carefully interpret data and avoid making incorrect conclusions.
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