Problem 1A Determination of Confounding Factors usinga Test of IndependenceAge and Obesity FrequenciesObeseNot obeseTotalAge500100600<5050+200200400Total1000300700A. Are age and obesity independent? Perform a y2 test of independence.Remember to document the five steps used in hypothesis testing.JONES& BARTLETT LEARNINGChart Your Own CourseO2011 Jones & Bartlett Learning, LLCwww.jblearning.com

Let us first test whether the “age” and “obesity” are independent or not, using a Chi-square test of…

Answered: Problem 1A Determination of Confounding…

Intermediate Algebra

10th Edition

ISBN:9781285195728

Author:Jerome E. Kaufmann, Karen L. Schwitters

Publisher:Jerome E. Kaufmann, Karen L. Schwitters

Chapter3: Polynomials

Section3.S: Summary

Problem 9S

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Problem B: Suppose that Cities A, B and C have the following observed number of COVID19 cases. Determine if the COVID19 cases for these barangays are homogeneous. City A B C COVID19 cases 400 450 500 What is the expected count of COVID19 cases in each city? What is the value of the computed test statistic? What is the critical value for this hypothesis testing procedure if the level of significance is 5%? What are the correct decision and appropriate conclusion?
Problem 2You’re looking into two manufacturers (A and B) from which to purchase a large number ofpaving slabs for a large-scale construction project. You may use one manufacturer as a backupif necessary, but only if there’s no significant difference in the weights of their paving slabs.Formulate and draw conclusions with ?? = 0.01 about a set of hypotheses using a nonparametrictest. Use the data in attached.
Problem 3You’re a healthcare engineering consultant and you’re analyzing the emergency room design at Pawhuska Hospital, Inc. Below you’ll find sample data for the waiting time (in minutes) of non-critical patients entering the emergency room.a. The hospital administrator wants to make the claim that average waiting time for non-critical patients is less than an hour. What is your opinion of that claim using the p-value approach? (note that you’d probably reject any null hypothesis if p-value < 0.1)b. In fact, you believe that at least a third of the non-critical patients arriving to the emergency room wait more than an hour. Test your claim with the critical value approach and 95% confidence. DATA: Obs Wait time 1 33.5 2 33.1 3 44.4 4 58.3 5 44.2 6 92.1 7 22.1 8 82.9 9 60.5 10 84.6 11 20.6 12 89.6 13 11.8 14 86.8 15 22.2 16 119.2 17 36.6 18 58.2 19 14.9 20 55.5 21 41.9 22 26.9 23 68.2 24 51.4 25 19.7 26 53.8 27 13.5 28…

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