Fifteen adult males between the ages of 35 and 50 participated in astudy to evaluate the effect of diet and exercise on blood cholesterollevels. The total cholesterol was measured in each subject initially andthen 5 months after participating in an aerobic exercise program andswitching to a low-fat diet, as shown in the table below. ePeople e1서 24 34 4터 54 6 74 84 9 10VariancleBefore e264 241 258 295 251 245 286 314 260 279 555.57After e228 232 227 240 238 241 234 256 247 23976.84(a) Calculate the (before and after) sample mean and standarddeviation; e(b) Calculate other relevant sample statistics, i.e, median, 1st and3rd quartiles, range and inter-quartile range; e(c) Construct a comparative box-plot for "before" and "after"cholesterol data and discuss your observations; -(d) Use tally charts / counts to calculate frequencies (use 5 bins)and construct histograms for the 2 sets of data; e

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Answered: Fifteen adult males between the ages 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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The following is data about the hemoglobin concentrations of volunteers collected at sea level and at an altitude of 11000 feet. sea level concentrations = [14.70 , 15.22, 15.28, 16.58, 15.10 , 15.66, 15.91, 14.41, 14.73, 15.09, 15.62, 14.92]11000 feet concentrations = [14.81, 15.68, 15.57, 16.59, 15.21, 15.69, 16.16, 14.68, 15.09, 15.30 , 16.15, 14.76] There are two alternative scenarios about the way the data were obtained. In scenario 1, there are 12 volunteers who lived for a month at sea level, at which time blood was drawn and the data in "sea level concentrations" dataset were obtained. Subsequently, all 12 volunteers were moved to 11000 ft and after a month the data in the "11000 feet concentrations" dataset obtained. There is a one to one correspondence between the numbers in the two datasets, that is the first numbers correspond to volunteer1, the second numbers to volunteer2 etc. In scenario 2, the "sea level concentrations" dataset is a random sample obtained from 12…
1. Data was collected for a sample of organic snacks. The amount of sugar (in mg) in each snack is summarized in the histogram below 12 10 2. 140 150 160 170 180 190 200 210 amount of sugar (mg) How many individuals are represented in the histogram? Frequency
From the data given below, calculate the gross and net reproduction rates : Age Group Female Population (in thousands) Female Live-births Survival Factor 15-19 1,399 15,133 0.9694 20-24 1,422 94,155 0.9663 25-29 1,521 102,676 0.9632 30-34 1,756 72,490 0.9584 35-39 1,451 31,402 0.9519 40-44 1,689 10,640 0.9424 45-49 1,667 700 0.9279
The table below shows data from a study relating a man's age to the average number of miles he can cover on foot in one hour. Age Miles 18 5.8 25 5.5 32 5.5 39 5.2 46 4.3 53 4.2 60 3.1 67 26 74 1.8
On occasion, medical studies need to model the proportion of the population that has a disease and compare that to observed frequencies of the disease actually occurring. Suppose the end-stage renal failure in south-west Wales was collected for different age groups. Do the data in the table show that the observed frequencies are in agreement with proportion of people in each age group? Test at the 1% level. Renal Failure Frequencies Age group 16-29 30-44 45-59 60-74 75+ Total Observed Frequencies 125 152 134 124 48 583 Expected Proportion 0.23 0.25 0.22 0.21 0.09 State the hypotheses.H0: The observed frequencies in agreement with proportion of people in each age group.Ha: The observed frequencies in agreement with proportion of people in each age group. Calculate the χ2 test statistic. Round expected values to two decimal places. Round χ2 to 3 decimal places.χ2 = Calculate the p-value. Round to 3 decimal places.p-value = State your decision.Since p-value α,…
Calculate the infant mortality rate (per 1000): Use the data in the table below to calculate the following vital statistics. Vital statistics Total midyear population Number of live births 4250 Total deaths (all causes) Deaths in infants under 1 year of age Deaths due to cancer 100 O 0.1 10 01 0.01 5,000,000 5000 In a clinical trial of 734 subjects treated with medicine A, 29 reported headaches. In a control group of 735 subjects not treated with medicine A, 117 reported headaches. The Number Needed to Treat is equal to: [ 02 09 06 3
The following is data about the hemoglobin concentrations of volunteers collected at sea level and at an altitude of 11000 feet. sea level concentrations = [14.70 , 15.22, 15.28, 16.58, 15.10 , 15.66, 15.91, 14.41, 14.73, 15.09, 15.62, 14.92]11000 feet concentrations = [14.81, 15.68, 15.57, 16.59, 15.21, 15.69, 16.16, 14.68, 15.09, 15.30 , 16.15, 14.76] There are two alternative scenarios about the way the data were obtained. In scenario 1, there are 12 volunteers who lived for a month at sea level, at which time blood was drawn and the data in "sea level concentrations" dataset were obtained. Subsequently, all 12 volunteers were moved to 11000 ft and after a month the data in the "11000 feet concentrations" dataset obtained. There is a one to one correspondence between the numbers in the two datasets, that is the first numbers correspond to volunteer1, the second numbers to volunteer2 etc. In scenario 2, the "sea level concentrations" dataset is a random sample obtained from 12…
Refer to the data presented in Exercise 2.86. Note that there were 50% more accidents in the 25 to less than 30 age group than in the 20 to less than 25 age group. Does this suggest that the older group of drivers in this city is more accident- prone than the younger group? What other explanation might account for the difference in accident rates?
An experiment sought to discover if a course on nutrition would influence the Body Mass Index (BMI) of the students enrolled. Measures of body fat percentages were taken before the yearlong course and then again at the end of the course for each of the 10 students. The data are as follows: Student: 1 2 3 4 5 6 7 8 9 10 Before: 16.85 18.62 35.79 22.66 18.74 22.25 19.95 14.61 27.49 20.00 End: 16.42 18.53 36.01 22.53 18.59 22.03 19.25 14.06 26.11 19.42 Test the hypothesis at the 0.05 level of significance that the mean body fat percentages of the students decreased by the end of the course.
A manufacturer of exercise equipment wanted to collect data on the effectiveness of their equipment. A magazine article compared how long it would take men and women to burn 200 calories during light or heavy workouts on various kinds of exercise equipment. The results summarized in the accompanying table are the average times for a group of physically active young men and women whose performances were measured on a representative sample of exercise equipment. Assume normality of the population. Complete parts (a) through (c) below. Click the icon to view the data table. C a) On average, how many minutes longer than a man must a woman exercise at a light exertion rate in order to burn 200 calories? Find a 95% confidence interval. minutes (Round to one decimal place as needed.) b) Estimate the average number of minutes longer a woman must work out at a light exertion than at heavy exertion to get the same benefit. Find a 95% confidence interval. (₁) minutes (Round to one decimal place…
The National Hurricane Center provides data that list the number of large (category 3, 4, or 5) hurricanes that have struck the United States, by decade, from 1851-2020. Is there sufficient evidence that the number of large hurricanes have remained constant (per decade)? What are the degrees of freedom? Decade Count Decade Count 1851-1860 6 1941-1950 10 1861-1870 1 1951-1960 8 1871-1880 7 1961-1970 6 1881-1890 5 1971-1980 4 1891-1900 8 1981-1990 5 1901-1910 4 1991-2000 5 1911-1920 7 2001-2010 8 1921-1930 5 2011-2020 10 1931-1940 8 Chi-squared test for given probabilitiesdata: stormsX-squared = 13.589, df = 16, p-value = 0.6293 A. 107 B. 17 C. 13.589 D. 16
Periodically, the county Water Department tests the drinking water of homeowners for contaminants such as lead and copper. The lead and copper levels in water specimens collected in 1998 for a sample of 10 residents of a subdevelopement of the county are shown below. lead (μμg/L) copper (mg/L) 4.4 0.643 2.4 0.57 1.5 0.46 2.6 0.895 5.9 0.2 3.4 0.54 3.8 0.245 1.6 0.583 5.7 0.769 1.7 0.215 (a) Construct a 9999% confidence interval for the mean lead level in water specimans of the subdevelopment. ≤μ≤

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