The second slide is the first part of the question and the first slide is the second part of the question (a) Develop the estimated regression equation that could be used to predict the percent audited given the average adjusted gross income reported (in dollars). (Round your value for the y-intercept to three decimal places and your value for the slope to six decimal places.)(b) At the 0.05 level of significance, determine whether the adjusted gross income (in dollars) and the percent audited are related. (Use the F test.)State the null and alternative hypotheses.O H,i A, 0O H: B 20O H: P=00+ °g:HFind the value of the test statistic. (Round your answer to two decimal places.)Find the p-value. (Round your answer to three decimal places.)pvalue =State your condlusion.O Reject H. We cannot condude that the relationship between the adjusted gross income (in dollars) and the percent audited is significant.O Do not reject H. We condlude that the relationship between the adjusted gross income (in dollars) and the percent audited is significant.O Reject H. We conclude that the relationship between the adjusted gross income (in dollars) and the percent audited is significant.O Do not reject H. We cannot condude that the relationship between the adjusted gross income (in dollars) and the percent audited is significant.(c) Did the estimated regression equation provide a good fit? Explain. (Round your answer to three decimal places.)Since 7 =isSelect-the estimated regression equation -Select=Va good fit.(d) Use the estimated regression equation developed in part (a) to calculate a 95% confidence interval for the expected percent audited for districts with an average adjusted gross income of $36,000. (Round your answers to two decimal place)% to% ne Transactional Records Access Clearinghouse at Syracuse University reported data showing the odds of an Internal Revenue Service audit. The following table shows the average adjusted gross income reported (in dollars) and theercent of the returns that were audited for 20 selected IRS districts.AdjustedGross Income ($)PercentDistrictAudītedLos Angeles36,6641.3Sacramento38,8451.1Atlanta34,8861.1Boise32,5121.1Dallas34,5311.0Providence35,9951.0San Jose37,7990.9Cheyenne33,8760.9Fargo30,5130.9New Orleans30,1740.9Oklahoma City30,0600.8Houston37,1530.8Portland34,9180.7Phoenix33,2910.7Augusta31,5040.7Albuquerque29,1990.6Greensboro33,0720.6Columbia30,8590.5Nashville32,5660.5Buffalo34,2960.5

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Description: The second slide is the first part of the question and the first slide is the second part of the question (a) Develop the estimated regression equation that could be used to predict the percent audited given the average adjusted gross income reporte

Given Information: The data represents the odds of an Internal Revenue Service audit. It shows the…

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- llansactional Records Access Clearinghouse at Syracuse University reported d cent of the returns that were audited for 20 selected IRS districts. Adjusted Gross Income ($) District Percent Audited Los Angeles 36,664 1.3 Sacramento 38,845 1.1 Atlanta 34,886 1.1 Boise 32,512 1.1 Dallas 34,531 1.0 Providence 35,995 1.0 San Jose 37,799 0.9 Cheyenne 33,876 0.9 Fargo 30,513 0.9 New Orleans 30,174 0.9 Oklahoma City 30,060 0.8 Houston 37,153 0.8 Portland 34,918 0.7 Phoenix 33,291 0.7 Augusta 31,504 0.7 Albuquerque 29,199 0.6 Greensboro 33,072 0.6 Columbia 30,859 0.5 Nashville 32,566 0.5

- llansactional Records Access Clearinghouse at Syracuse University reported d cent of the returns that were audited for 20 selected IRS districts. Adjusted Gross Income ($) District Percent Audited Los Angeles 36,664 1.3 Sacramento 38,845 1.1 Atlanta 34,886 1.1 Boise 32,512 1.1 Dallas 34,531 1.0 Providence 35,995 1.0 San Jose 37,799 0.9 Cheyenne 33,876 0.9 Fargo 30,513 0.9 New Orleans 30,174 0.9 Oklahoma City 30,060 0.8 Houston 37,153 0.8 Portland 34,918 0.7 Phoenix 33,291 0.7 Augusta 31,504 0.7 Albuquerque 29,199 0.6 Greensboro 33,072 0.6 Columbia 30,859 0.5 Nashville 32,566 0.5

Algebra & Trigonometry with Analytic Geometry

13th Edition

ISBN:9781133382119

Author:Swokowski

Publisher:Swokowski

Chapter7: Analytic Trigonometry

Section7.6: The Inverse Trigonometric Functions

Problem 94E

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