### Peak Heart Rate Data AnalysisPeak heart rate (beats per minute) was determined both during a shuttle run and during a 300-yard run for a sample of $ n = 10 $ individuals with Down syndrome. This study was documented in "Heart Rate Responses to Two Field Exercise Tests by Adolescents and Young Adults with Down Syndrome," Adapted Physical Activity Quarterly [1995: 43–51], resulting in the following data:#### Data- **Shuttle Run:** - 168, 168, 188, 172, 184, 176, 192, 172, 188, 180- **300-Yard Run:** - 184, 192, 200, 192, 188, 180, 182, 188, 196, 196#### Questions1. **Scatterplot Construction:** - Construct a scatterplot of the data. - Analyze what the scatterplot suggests about the nature of the relationship between the two variables (shuttle run peak rate and 300-yard peak rate).2. **Correlation Calculation (Part a):** - Let $ x $ represent the shuttle run peak rate and $ y $ the 300-yard run peak rate. - Calculate the correlation coefficient $ r $. - Determine if the value of $ r $ is consistent with insights from the scatterplot.3. **Correlation Comparison (Part b):** - Let $ x $ represent the 300-yard peak rate and $ y $ the shuttle run peak rate. - Compare how the value of $ r $ differs from the calculation in Part (a).#### Explanation of Accompanying Graphs/Diagrams- **Scatterplot:** - This graph visually represents the relationship between the two peak heart rates for each individual. Each point corresponds to one pair of shuttle and 300-yard run peak heart rates. The pattern or trend shown by the points can suggest correlation strength and direction.To interpret the scatterplot and calculate the correlation, use statistical software or a calculator capable of statistical functions.

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Answered: Peak heart rate (beats per minute) was…

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…
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Consider the following measurements of blood hemoglobin concentrations (in g/dL) from three human populations at different geographic locations: population1 = [ 14.7 , 15.22, 15.28, 16.58, 15.10 ] population2 = [ 15.66, 15.91, 14.41, 14.73, 15.09] population3 = [ 17.12, 16.42, 16.43, 17.33] Perform ANOVA to check if any of these populations have different mean hemoglobin concentrations. (Assume that all the ANOVA requirements such as normality, equal variances and random samples are met.) After you perform ANOVA perform a Tukey-Kramer post-hoc test at a significance level of 0.05 to see which populations actually have different means. As usual, round all answers to two digits after the decimal point. (Make sure you round off to at least three digits any intermediate results in order to obtain the required precision of the final answers.) For any questions, which ask about differences in means or test statistics, which depend on differences in means provide absolute values. In…
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…
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