Here is my question: How large a sample of students would be needed in order to estimate the population prediction mean within ±2 with 85% confidence? Given that the sample of wight students predictions was 72 83 78 65 69 77 81 71 that I have calculated the sample standard deviation(s) = 6.2335, the sample mean = 74.5 and the sample size is 8.
In my own trial, 85% refers to z=1.440. The question requires my calculation base on t(20,0.075) but I cannot find the 0.075 in the table. So I doubt whether my directions aren't correct.
Thanks a lot for help!
Here is a simulation that serves as a 'reality check' on my answer in Comments that the necessary sample size is around 20 or 22.
In R, the procedure
t.testwith parameterconf.lev=.85)will use dataxshow an 85% confidence interval for the population mean $\mu.$.Suppose, for planning purposes, we use the sample mean and SD from your pilot experiment with eight observations to be the population mean and SD. Then we can simulate vector
xof $n=22$ observations from $\mathsf{Norm}(\mu=74.5, \sigma=6.23).$ And uset.testto find the resulting 85% CI for $\mu.$ Finally, we can find the half-length of the CI to be the margin of error $E$ and see how close it is to $E = 2.$The result is a little larger than we hoped. But this is only for one sample. If we do this for 10,000 samples and average the results, we can get an idea whether $n = 22$ is, on average, sufficient to have a margin of error of the desired size.
So margins of error are often as small as 1.5 or as large as 2.3, but they are mostly near 2.0, as desired.