Step 2The x test statistic for a goodness of fit follows where f; is the observed frequency for category i, e;expected frequency for category i, and k is the number of categories. The appropriate x has kis the1 degrees offreedom.k= (f, - e)?i = 1The observed and expected frequencies are summarized in the table below.ExpectedFrequencySquaredDifferenceSquared DifferenceDivided by ExpectedObservedDifferenceCategoryFrequency(fj – e;)²eijfij - eij(fj – @j)²fjeijFrequency(-60)23,6003,600A20802080 = -60%D80В1608080204040010The sum of the final column will be the x test statistic. Thus, the test statistic is x=There are k= 3 categories, so the degrees of freedom is k – 1 =Cubri4Cli (a) Use the p-value approach.A goodness of fit test will be conducted for the following hypotheses. This type of test is always an upper tailtest. The p-value approach will be used, meaning that the given level of significance, a =0.01, will becompared to the area under the curve to the right of the calculated test statistic.0.40, PB = 0.40, and= 0.20Ho:PAH: The population proportions are not pa = 0.40, pB = 0.40, and pcPc= 0.20.The goal of the hypothesis test is to determine if the observed proportions are significantly different from thegiven proportions. A sample size of 200 yielded 20 in category A, 160 in category B, and 20 in category C.Assuming the hypothesized proportions are true, then the expected frequencies in each category will be theproduct of the hypothesized proportions and the sample size.expected frequency = category proportion(sample size)The proportion for category A is assumed to be 0.40. Use the sample size of 200 to find the expectedfrequency for this category, ea•expected frequencycategory proportion(sample size)%DCA =0.400.40 (200)8080The proportion for category B is assumed to be 0.40. Use the sample size of 200 to find the expectedfrequency for this category, eg.expected frequencycategory proportion(sample size)eB =0.400.40 (200)8080The proportion for category C is assumed to be 0.20. Use the sample size of 200 to find the expectedfrequency for this category, ec:expected frequencycategory proportion(sample size)%Dec = (0.200.20)(200)4040

χ2 test is popularly known as the test of goodness of fit for the reason that it enables us to…

Expected Frequency Squared Difference Squared Difference Divided by Expected Observed Difference Category Frequency fij - eij (fj – @;)² ej Frequency (-60)2 : 3,600 3,600 A 20 80 20 – 80 = -60 80 В 160 80 80 C 20 40 400 10 The sum of the final column will be the x test statistic. Thus, the test statistic is x %3D There are k = 3 categories, so the degrees of freedom is k – 1 =

Expected Frequency Squared Difference Squared Difference Divided by Expected Observed Difference Category Frequency fij - eij (fj – @;)² ej Frequency (-60)2 : 3,600 3,600 A 20 80 20 – 80 = -60 80 В 160 80 80 C 20 40 400 10 The sum of the final column will be the x test statistic. Thus, the test statistic is x %3D There are k = 3 categories, so the degrees of freedom is k – 1 =

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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Over doses from opioids have captured the national spotlight. Rightly so they kill nearly 30,000 Americas a year and cause more than 1 million hospitalizations. However, the misuse of over-the-counter pain medications (e.g. Tylenol, Advil, Aleve) can cause stomach bleeding, ulcers, liver disease and, in some cases, death. Approximately 80% of Americans use these medications to relieve headaches, backaches, sore muscles, and reduce fever but they are unaware of the dangers if the drugs are not used correctly. A random sample (n=101) of adults were given a questionnaire to ask the question "How often do you use pain medication in one day?". Using the output, histogram, box- whisker plot, and the QQ Plot attached - check the assumption of normality for this data. PainNormalityInformationoutputhistbox 210317.pdf The assumption of normality was checked by comparing the and the median. This suggests that the distribution is slightly The + The is between the acceptable range of -3 and +3.…
T-TEST FOR INDEPENDENT MEANS 1. Two types of instruments for measuring the amount of sulfur monoxide in the atmosphere are being compared in an air pollution experiment. It is desired to determine whether the types of instruments yield measurement having the same variability. The following readings were recorded for the instrument. Sulfur Monoxide Instrument A Instrument B 0.86 0.87 0.82 0.74 0.75 0.63 0.61 0.55 0.89 0.76 0.64 0.70 0.81 0.69 0.68 0.57 0.65 0.53 Assuming the population of measurements to be approximately normally distributed, test the null hypothesis using two tailed test at 0.05 level of significance.
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The coefficient of variation for the male pulse rates is __ % The coefficient of variation for the female pulse rates is __%
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