tutu In physiology, an objective measure of aerobic fitness is how efficiently the body can absorb and use oxygen (oxygen consumption). A physiologist, Dr. Castillejo, conducted a research wherein subjects participated in a predetermined exercise run of 1.5 miles. Measurements of oxygen consumption as well as several other variables such as age, gender, runtime, resting and maximum pulse rates, and weight were recorded from 50 randomly selected gym members. Dr. Castillejo is interested in determining whether any of these other variables can help predict oxygen consumption. She believes that a possible link between these factors will help her determine how to improve the health of her gym members. Help Dr. Castillejo in developing a proposal for the improvement of her gym members' health condition. The variables are described below. gender- either male or female runtime - time to run 1.5 miles (in min) age - age of the gym member in years weight - weight of the gym member (in kg) oxygen consumption - measure of the ability to use oxygen in the blood stream (in ml/min) rest pulse - resting pulse rate (in bpm) maximum pulse - maximum pulse rate during the run (in bpm) According to the study of Fitbit, a company producing fitness trackers, women typically have higher resting heart rates. Use the R commander output below to test if the same result applies to Dr. Castillejo's gym members. Write a brief report about the analysis by identifying the set of hypotheses to be tested, the appropriate test to use, and implications and recommendations of/from the conclusions. R COMMANDER OUTPUT R COMMANDER OUTPUT Shapiro-Wilk normality test data: restpulse male Shapiro-Wilk normality test data: restpulse_female W = 0.94898, p-value = 0.17212 W = 0.96948, p-value = 0.72155 R COMMANDER OUTPUT F test to compare two variances data: restpulse_male and restpulse_female F = 1.3110, num df = 20, denom df = 28, p-value = 0.5002 Alternative hypothesis: true ratio of variances is not equal to 1 R COMMANDER OUTPUT parametric test data: restpulse_female and restpulse_male (Female - Male) t = 0.94747, df = 48, p-value = 0.174123 alternative hypothesis: true difference in means is greater than 0 R COMMANDER OUTPUT non-parametric test data: restpulse_female and restpulse_male (Female Male) Z = -0.84521, df = 48, p-value = 0.19766 alternative hypothesis: true location shift is greater than 0

tutu In physiology, an objective measure of aerobic fitness is how efficiently the body can absorb and use oxygen (oxygen consumption). A physiologist, Dr. Castillejo, conducted a research wherein subjects participated in a predetermined exercise run of 1.5 miles. Measurements of oxygen consumption as well as several other variables such as age, gender, runtime, resting and maximum pulse rates, and weight were recorded from 50 randomly selected gym members. Dr. Castillejo is interested in determining whether any of these other variables can help predict oxygen consumption. She believes that a possible link between these factors will help her determine how to improve the health of her gym members. Help Dr. Castillejo in developing a proposal for the improvement of her gym members' health condition. The variables are described below. gender- either male or female runtime - time to run 1.5 miles (in min) age - age of the gym member in years weight - weight of the gym member (in kg) oxygen consumption - measure of the ability to use oxygen in the blood stream (in ml/min) rest pulse - resting pulse rate (in bpm) maximum pulse - maximum pulse rate during the run (in bpm) According to the study of Fitbit, a company producing fitness trackers, women typically have higher resting heart rates. Use the R commander output below to test if the same result applies to Dr. Castillejo's gym members. Write a brief report about the analysis by identifying the set of hypotheses to be tested, the appropriate test to use, and implications and recommendations of/from the conclusions. R COMMANDER OUTPUT R COMMANDER OUTPUT Shapiro-Wilk normality test data: restpulse male Shapiro-Wilk normality test data: restpulse_female W = 0.94898, p-value = 0.17212 W = 0.96948, p-value = 0.72155 R COMMANDER OUTPUT F test to compare two variances data: restpulse_male and restpulse_female F = 1.3110, num df = 20, denom df = 28, p-value = 0.5002 Alternative hypothesis: true ratio of variances is not equal to 1 R COMMANDER OUTPUT parametric test data: restpulse_female and restpulse_male (Female - Male) t = 0.94747, df = 48, p-value = 0.174123 alternative hypothesis: true difference in means is greater than 0 R COMMANDER OUTPUT non-parametric test data: restpulse_female and restpulse_male (Female Male) Z = -0.84521, df = 48, p-value = 0.19766 alternative hypothesis: true location shift is greater than 0

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter4: Eigenvalues And Eigenvectors

Section4.6: Applications And The Perron-frobenius Theorem

Problem 22EQ

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