Ah artičlé in thế Journal of Sports Science (1987, Vol. 5, pp. 261-271) presents results of an investigation of the hemoglobin level of Canadian Olympic ice hock players. The data reported are as follows (in g/dl): 15.3 16.0 14.4 16.2 16.2 14.9 15.7 15.3 14.6 15.7 16.0 15.0 15.7 16.2 14.7 14.8 14.6 15.6 14.5 15.2

Ah artičlé in thế Journal of Sports Science (1987, Vol. 5, pp. 261-271) presents results of an investigation of the hemoglobin level of Canadian Olympic ice hock players. The data reported are as follows (in g/dl): 15.3 16.0 14.4 16.2 16.2 14.9 15.7 15.3 14.6 15.7 16.0 15.0 15.7 16.2 14.7 14.8 14.6 15.6 14.5 15.2

Calculus For The Life Sciences

2nd Edition

ISBN:9780321964038

Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.

Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.

Chapter1: Functions

Section1.2: The Least Square Line

Problem 5E

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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…
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 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 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 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 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…
assume that the data was obtained from two indepen-dent samples. That is, 28 subjects were enrolled into the study, and half were randomly assignedto the corn flakes diet, and half to the oat bran diet. After two weeks the LDL cholesterol level ofeach individual was recorded. LDL (mmol/l)Subject Corn Flakes Oat Bran1 4.61 3.842 6.42 5.573 5.40 5.854 4.54 4.805 3.98 3.686 3.82 2.967 5.01 4.418 4.34 3.729 3.80 3.4910 4.56 3.8411 5.35 5.2612 3.89 3.7313 2.25 1.8414 4.24 4.14 Questions; a) What are the appropriate null and alternative hypotheses for a two-sided test?(b) Conduct the test at the 0.05 level of significance. What is the p-value?(c) Construct a 95% confidence interval.
In two wards for elderly women in a geriatric hospital the following levels of haemoglobin were found: Ward A: 12.2, 11.1, 14.0, 11.3, 12.5, 12.7, 13.4, 13.7 g/dl; Ward B: 11.9, 10.7, 12.3, 13.9, 11.4, 12.0, 11.1 g/dl. What is the 95% confidence interval for the difference in treatments? (Table value = 2.16)
A large manufacturing company producing air conditioner compressor believes the number of units of air conditioner sold is related to atmospheric temperature. An R&D officer conducted a study and gathered the following data: 3. Day Sale Temperature (Fahrenheit) 63 (in thousands) 1.52 1 2 70 1.68 3 73 1.8 4 75 2.05 80 2.36 6. 82 2.25 7 85 2.68 8 88 2.9 9. 90 3.14 3.06 3.24 10 91 11 92 12 75 1.92 13 98 3.4 14 100 3.28 Construct an estimated regression line between temperature and number of units sold. а) b) Does the model in part (a) confirm that contribution of temperature to number of units of air conditioner sold? Test using a 0.05. Find the coefficient of correlation. What does the value imply about the relationship of the two variables? c) If the temperature soared to 120 Fahrenheit, can you predict the number of units of air conditioner sold? Explain d)
D. A study aims to determine the relationship of salt intake to the blood pressure of persons aged 15 years and over. The mean systolic blood pressure (SBP) of 20 subjects with a low salt diet was compared to that of an equal number of subjects with a high salt diet. The following data were generated: High Salt Diet Low Salt Diet Mean SBP 138 mmHg 120 mmHg Std. dev. of SBP 11.9 mmHg 12.2 mmHg Is there a difference between the means of systolic blood pressure of subjects with high and low salt diets?
The blood lead concentrations, in micrograms per deciliter (µg/dL), of 20 children from two different neighborhoods were measured. The results are recorded in the table. Neighborhood 1 3.97 3.92 3.99 3.71 4.13 3.97 4.02 3.88 4.12 3.70 3.96 3.78 4.30 4.09 4.13 4.94 3.93 3.95 3.86 3.83 Neighborhood 2 4.32 4.23 3.78 4.10 4.35 4.21 4.36 4.21 4.02 4.05 4.29 4.12 4.59 4.12 4.02 3.85 3.97 4.28 4.39 4.14 Using the same scale, draw a box-and-whisker plot for each of the two data sets, placing the second plot below the first. Considering that high blood lead concentrations are harmful to humans, in which of the two neighborhoods would you prefer to live? neighborhood1 or neighborhood 2
a. Compute the correlation coefficient between radiation dose and exposure time.