Homework #5 - Due Thursday, March 16th, at the beginning of lab
NAME: Carli White
b) Describe the association between respiratory rate and age in one or two sentences and in the context of the problem.
The older the person becomes, the lower the respiratory rate becomes between 0 to 35 years of age.
d) Use StatCrunch to compute the regression model with log (respiratory rate) as the response variable and age as the explanatory variable and write the resulting regression equation in the context of the problem.
log10(Rate) = 1. 6699138 - 0. 0083 Age Regression Equation:
e) What proportion of the variation in log (respiratory rate) is explained by the regression model of log (respiratory rate) on age?
The proportion of log (respiratory rate) of age is 52. 01 percent.
f) Carefully interpret the slope of the regression model (from part d) in terms of how the respiratory rate (NOT the log (respiratory rate)) changes per 1-month increase in age.
This plot tells us about the linear regression model that from ages 0 to 10, the plots are closer together. Then from ages 10 to 35 the residuals start to slowly branch out in some areas.
h) For a child of age 7 months, what is the predicted respiratory rate in breaths per minute?
Log10 (Rate)=1. 6699-. 0083(. 7) =1. 66409 10^1. 66409=46. 14 breaths per second i) Predict the respiratory rate (again in breaths per minute) for a child of age 7 years. How confident are you in this prediction? Explain.
Log10(Rate)=1. 6699-. 0083(7) =1. 6118 10^1. 6118=40. 91 breaths per minute j) Suppose when Superman was a child of age 24 months, he had a respiratory rate of 90 breaths per minute. Relative to the rest of the data, explain clearly in one sentence for each:
whether this child is an outlier:
whether this child has high leverage:
whether this child has high influence on the regression model:
a) Identify the "component" to be repeated. Describe/show how you will model this component's outcome using the random num...