Fifteen adult males between the ages of 35 and 50 participated in a study to evaluate the effect ofdiet and exercise on blood cholesterol levels. The total cholesterol was measured in each subjectinitially and then three months after participating in an aerobic exercise program and switching toa low-fat diet. The data are shown in the following table:Blood Cholesterol LevelBeforeSubjectAfter126522922402313258227429524052512386245m241234728783142569260247102792391128324612240132382182192262331422515247Do the data support the claim that low-fat diet and aerobic exercise are of value in producing amean reduction in blood cholesterol levels? Use a = 0.05a. Fail to reject the Null Hypothesis. 5.465 > 1.753b. Reject the Null Hypothesis. 5.465 > 1.761c. None among the choicesd. Reject the Null Hypothesis. 5.465 > 1.753

Answered: Image /qna-images/answer/9260a77b-53b0-4950-8f4a-d18b6c5fa10d.jpg

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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Analyze the data and write a short report. Your report must contain A frequency distribution of respondents’ age, gender and race. Age Frequency 17 6 18 6 19 5 20 3 Gender Frequency Female 9 Male 11 Race Frequency African 6 Chinese 2 Indian 12 Tables showing the total average consumption of the three types of foods and the two types of drinks. Food Total Consumption Percentage African 36 46.15% Chinese 32 41.03% Indian 10 12.82% Drinks Total Consumption Percentage Juice 44 60.27% Water 29 39.72% Cross-tabulation of the respondent’s Age and sex with drink preference. JUICE Sex Total Age Female Male 17 1 3 4 18 2 2 4 19 1 0 1 20 3 0 3 TOTAL 7 5 12…
The following data are collected from pregnant women to compare the Plasma ascorbic acid level of smokers and non-smokers. Table: Plasma ascorbic acid values Non-smokers 0.97, 0.72, 1.00, 0.81, 0.62, 1.32, 1.14, 1.22, 0.90, 0.74, 0.88, 0.94 Smokers 0.88, 0.71, 0.98, 0.79, 1.01, 1.16, 0.78, 1.28 Test whether there is any difference between plasma ascorbic acid levels of smokers and non-smokers. Also find 95% confidence interval for the difference of two means. Describe your findings. Use alpha=0.05 [Hint: use hypothesis, test statistics confidence interval etc.]
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…
The alcohol content of wine depends on the grape variety, the way in which the wine is produced from the grapes, the weather, and other influences. Here are data on the percent of alcohol in wine produced from the same grape variety in the same year by 16 winemakers in the same region of Italy: 12.86 12.88 12.81 12.70 12.51 12.60 12.25 12.53 13.49 12.84 12.93 13.36 13.52 13.62 12.25 13.16 Give a 95% confidence interval for the mean alcohol content of wine of this type.
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.
The following table shows some data from a study on substance use among 10th graders in the United States and Europe. Smoked Cigarettes Cigarette-Free Totals U.S. 14,000 Europe 96,000 Total 71,210 110,000
A healthcare provider monitors the number of CAT scans perfomed each month in each of its clinics. The most recent year of data for a particular clinics follows (the reported variable is the number of CAT scans each month expressed as the number of CAT scans per thousand members of the health plan): 2.31, 2.09, 2.36, 1.95, 1.98, 2.25, 2.16, 2.07, 1.88, 1.94, 1.97, 2.02. Find a two-sided 95% confidence interval for the standard deviation. What should you do to address any reservations about this confidence interval? Round your answers to two decimal places (e.g. 98.76).
A sample of 15, 10 years -old children was taken to study whether watching television reduces the amount of physical exercise, causing weight gains. The number of kilograms each child was overweight by was recorded (a negative number indicates the child is underweight). In addition, the number of hours of television viewing per week was also recorded. These data are listed in the table below. Televisioin hours 42 34 25 35 37 38 31 33 19 29 38 28 29 36 18 Overweight (kg) 8 3 0 0 6 6 3 3 -4 4 4 2 1 6 -3 a. Use an appropriate plot to investigate the relationship between Television(hours) and Overweight (KG). briefly explain the selection of each variable on the X and Y axes and why?b. Calculate and interpret the coefficient of correlation (r) betweenTelevision(hours) and Overweight (KG).
Cholesterol level data (in mg/dL) were collected on patients four days after having a heart attack. The data are in the table below. Determine if the data are from a population that is normally distributed. 142 160 186 206 210 220 224 226 236 242 244 266 270 272 276 278 294 310 318 360
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…
In a study conducted in Italy, 10 patients with hypertriglyceridemia were placed on a low-fat, high-carbohydrate diet. Before the start of the diet, cholesterol and triglyceride measurements were recorded for each subject. Patient Cholesterol Level (mmol/l) Triglyceride level (mmol/l) 1 5.12 2.30 2 6.18 2.54 3 6.77 2.95 4 6.65 3.77 5 6.36 4.18 6 5.90 5.31 7 5.48 5.53 8 6.02 8.83 9 10.34 9.48 10 8.51 14.20 a. Construct a two-way scatter plot for these data. b. Use STATA to calculate Pearson’s Correlation Coefficient for these data. c. Test, α = 0.05, whether or not the population correlation, ρ, equals 0.
A psychologist believed that as children get older, they engage in more “inactive activities” such as playing computer games, watching TV and surfing the internet. She collected data from 10 children. She recorded the age of each child and the amount of activity (in hours) the child engaged in per week. Age Activity 7 4.3 9 3.2 10 1 13 1.5 12 1.2 15 0.8 9 3 12 4 15 1.5 14 1.9 Using excel, obtain a scatterplot of the data. Discuss the relationship between age and activity based on the scatterplot. Using excel, obtain the simple linear regression linear regression line predicting activity from age. Interpret the intercept and slope of the regression line. By hand, predict the amount of activity for age = 14. By hand, calculate the residual for age = 14 Using excel output, test the null hypothesis that the slope coefficient is zero using the p-value approach. Write one sentence interpreting the meaning of this result. Make sure to report the test statistic…

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