### False Alarm Analysis**Introduction:**The data below represents the number of false fire alarms recorded each month at several sites.**Data Table:**| Month | Number of Alarms ||------------|------------------|| January | 32 || February | 15 || March | 37 || April | 38 || May | 45 || June | 48 || July | 46 || August | 42 || September | 34 || October | 36 || November | 28 || December | 26 |**Source:**Journal of Architectural Engineering 5:62–65**Hypothesis Testing:**Evaluate the hypothesis that false alarms are equally probable in any given month using a significance level (\(\alpha\)) of 0.01. **Crime Rates**The FBI computed the proportion of violent crimes in the United States falling into each of four categories. A simple random sample of 500 violent crimes committed in California was categorized similarly. The table below presents the results:| Category | U.S. Proportion | California Frequency ||---------------------|-----------------|----------------------|| Murder | 0.013 | 5 || Forcible Rape | 0.051 | 23 || Robbery | 0.360 | 206 || Aggravated Assault | 0.576 | 266 |Can you conclude that the proportions of crimes in the various categories in California differ from the United States as a whole? Use the 0.05 level of significance.

Name: ### False Alarm Analysis**Introduction:**The data below represents th
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Description: ### False Alarm Analysis**Introduction:**The data below represents the number of false fire alarms recorded each month at several sites.**Data Table:**| Month | Number of Alarms ||------------|------------------|| January | 32

Hey, since there are multiple questions posted, we will answer first question. If you want any specific question to be answered then please submit that question only or specify the question number in your message. The hypotheses are given below: Null hypothesis: H0: The false alarms are equally likely to occur in any month. Alternate hypothesis: H1: The false alarms are not equally likely to occur in any month. Step-by-step procedure to find the test statistic and P-value using MINITAB: In Stats, select Tables and choose Chi-square Goodness of Fit Test (one variable). In Observed count, select Number of Alarms. In Proportion, Choose Equal proportion. Click Ok.Output obtained using Excel is given below: From the output, the test statistics is 27.7916 and the P-value is 0.003. Decision rule: If the P-value of the test is less than the level of significance, reject H0. Otherwise, fail to reject the null hypothesis H0. Conclusion: The level of significance is 0.01 and the P-value is 0.003. Here, P-value is less than the level of significance. Thus, the decision is “reject the null hypothesis”. Therefore, there is no evidence to conclude that the false alarms are equally likely to occur in any month

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False alarm: The numbers of false fire alarms were counted each month at a number of sites. The results are given in the following table. Month Number of Alarms January 32 February 15 March 37 38 April May 45 June 48 July August 46 42 September 34 October 36 November 28 December 26 Source: Journal of Architectural Engineering 5:62-65 Test the hypothesis that false alarms are equally likely to occur in any month. Use the a = 0.01 level of

False alarm: The numbers of false fire alarms were counted each month at a number of sites. The results are given in the following table. Month Number of Alarms January 32 February 15 March 37 38 April May 45 June 48 July August 46 42 September 34 October 36 November 28 December 26 Source: Journal of Architectural Engineering 5:62-65 Test the hypothesis that false alarms are equally likely to occur in any month. Use the a = 0.01 level of

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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