We take a random sample of bone density measurements from 16 American college fe
ID: 3252616 • Letter: W
Question
We take a random sample of bone density measurements from 16 American college females. The measurements are as follows (In gm/cm3): 1.085, 1.041, 1.075, 1.034, 1.050, 1.055, 1.070, 1.090 1.072, 1.083, 1.081, 1.051, 1.051, 1.048, 1.051, 1.033 It is reasonable to treat these measurements as coming from a normal distribution with unknown mean mu and unknown variance sigma^2 a)Use the data to calculate an unbiased point estimate of the true mean bone density, mu, of American College females. b) Use the data to find an unbiased point estimate of the population variance, sigma^2 of bone density of American College females. c) Find the sample standard deviation of the above data d) Create a 90% confidence interval for mu. e) What critical value did you use to calculate the 90% confidence interval in d? f) Create a 90% prediction interval for mu. g) Copy your R script for the above into the text box here.Explanation / Answer
The complete R snippet is as follows
df<- c(1.085,1.041,1.075,1.034,1.050,1.055,1.070,1.090,1.072,1.083,1.081,1.051,1.051,1.048,1.051,1.033)
## mean
mean(df)
## variance
sd(df)^2
## standard deviation of the sample
sd(df)/sqrt(length(df))
## 90% confidence interval
mean(df) + 1.644*sd(df)/sqrt(length(df)) ## upper limit
mean(df) - 1.644*sd(df)/sqrt(length(df)) ### lower limit
## the critical value is 1.645
##using
qnorm(1-(1-0.90)/2)
############
The results are
> df<- c(1.085,1.041,1.075,1.034,1.050,1.055,1.070,1.090,1.072,1.083,1.081,1.051,1.051,1.048,1.051,1.033)
> ## mean
> mean(df)
[1] 1.060625
> ## variance
> sd(df)^2
[1] 0.00034905
> ## standard deviation of the sample
> sd(df)/sqrt(length(df))
[1] 0.00467072
> ## 90% confidence interval
> mean(df) + 1.644*sd(df)/sqrt(length(df)) ## upper limit
[1] 1.068304
> mean(df) - 1.644*sd(df)/sqrt(length(df)) ### lower limit
[1] 1.052946
> ## the critical value is 1.645
> ##using
> qnorm(1-(1-0.90)/2)
[1] 1.644854
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