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 people living at sea level and the "11000 feet concentrations" dataset is a random sample obtained from 12 different people living at 11000 feet. In this case there is no correlation between the individual numbers in the two datasets. PART A- In scenario 2, what is the width (upper bound - lower bound) of the 95% confidence interval for the difference of the mean hemoglobin concentrations between the two samples? Input the absolute value (if you get a negative number input - that number). PART B- In scenario 2, what is the absolute value of the t-statistic required to carry out an appropriate t-test to check if altitude has an effect on hemoglobin concentrations
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 people living at sea level and the
"11000 feet concentrations" dataset is a random sample obtained from 12 different people living at 11000 feet. In this case there is no
PART A- In scenario 2, what is the width (upper bound - lower bound) of the 95% confidence interval for the difference of the
PART B- In scenario 2, what is the absolute value of the t-statistic required to carry out an appropriate t-test to check if altitude has an effect on hemoglobin concentrations?
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