21
n = 35
xbar = 18.4
s = 4.5
t_critical = qt(.975, n - 1)
lower = xbar - t_critical*s/sqrt(n)
upper = xbar + t_critical*s/sqrt(n)
(answer = c(lower,upper))
## [1] 16.8542 19.9458
n = 50
xbar = 18.4
s = 4.5
t_critical = qt(.975, n - 1)
lower = xbar - t_critical*s/sqrt(n)
upper = xbar + t_critical*s/sqrt(n)
(answer = c(lower,upper))
## [1] 17.12111 19.67889
n = 35
xbar = 18.4
s = 4.5
t_critical = qt(.995, n - 1)
lower = xbar - t_critical*s/sqrt(n)
upper = xbar + t_critical*s/sqrt(n)
(answer = c(lower,upper))
## [1] 16.32468 20.47532
It appears the margin of error increases.
23
A confidence interval is NOT a probability interval.
Correct
A confidence interval is NOT a census.
We are making a statement about the population parameter of the whole country, NOT just Idaho.
25
They are 90% confident that Taco Bell’s mean drive through time is between 161.5 and 164.7 seconds
27
To increase the precision of the interval, you can decrease the level of confidence so it encompasses a more specific amount of the data or increase the sample size
29
The sample size must be large so that the sample mean’s distribution will be normal
The sample size is less than 5% of the population
n = 51
xbar = .167
s = .01
t_critical = qt(.95, n - 1)
lower = xbar - t_critical*s/sqrt(n)
upper = xbar + t_critical*s/sqrt(n)
(answer = c(lower,upper))
## [1] 0.1646533 0.1693467
31
n = 1006
xbar = 13.4
s = 16.6
t_critical = qt(.995, n - 1)
lower = xbar - t_critical*s/sqrt(n)
upper = xbar + t_critical*s/sqrt(n)
(answer = c(lower,upper))
## [1] 12.04932 14.75068
There is a 99% confidence level that the mean number of books read in the past year by Americans is between 12.05-14.75
33
n = 81
xbar = 4.6
s = 15.9
t_critical = qt(.975, n - 1)
lower = xbar - t_critical*s/sqrt(n)
upper = xbar + t_critical*s/sqrt(n)
(answer = c(lower,upper))
## [1] 1.084221 8.115779
There is a 95% confidence level that the mean incubation period of Severe Acute Respiratory Syndrome patients is between 1.08-8.12 days
5
n = 20
(small_value = qchisq(.05, n-1))
## [1] 10.11701
(large_value = qchisq(.95, n-1))
## [1] 30.14353
7
n = 23
(small_value = qchisq(.01, n-1))
## [1] 9.542492
(large_value = qchisq(.99, n-1))
## [1] 40.28936
9
n = 20
ssquared = 12.6
small_value = qchisq(.05, n-1)
large_value = qchisq(.95, n-1)
lower = (n-1)*ssquared/large_value
upper = (n-1)*ssquared/small_value
(answer = c(lower,upper))
## [1] 7.942004 23.663111
n = 30
ssquared = 12.6
small_value = qchisq(.05, n-1)
large_value = qchisq(.95, n-1)
lower = (n-1)*ssquared/large_value
upper = (n-1)*ssquared/small_value
(answer = c(lower,upper))
## [1] 8.586138 20.634315
The width of the interval increases
n = 20
ssquared = 12.6
small_value = qchisq(.01, n-1)
large_value = qchisq(.99, n-1)
lower = (n-1)*ssquared/large_value
upper = (n-1)*ssquared/small_value
(answer = c(lower,upper))
## [1] 6.614928 31.364926
The width of the interval increases
11
n = 10
ssquared = (2.343)^2
small_value = qchisq(.025, n-1)
large_value = qchisq(.975, n-1)
lower = (n-1)*ssquared/large_value
upper = (n-1)*ssquared/small_value
(answer = sqrt(c(lower,upper)))
## [1] 1.611598 4.277405
There is a 95% confidence level that the population’s standard deviation of prices is between 1.612-4.278
13
n = 14
ssquared = (1114.412)^2
small_value = qchisq(.05, n-1)
large_value = qchisq(.95, n-1)
lower = (n-1)*ssquared/large_value
upper = (n-1)*ssquared/small_value
(answer = sqrt(c(lower,upper)))
## [1] 849.6926 1655.3548
There is a 90% confidence level that the population’s standard deviation of cost is between 849.7-1655.3