Notes

First we must determine whether all of our conditions are adequately satisfied. We do have more than 10 successes and 10 failures, our data sets are independent of each other, our 10% condition is satisfied, and our data was collected randomly. Now we can start to analyze and begin making calculations. Unlike confidence intervals we already know p which is .3, but now we are faced with the challenge of seeing how relatable the two data sets are.

Ho: p=.3 and for Halt: p>.32

Using 95% confidence I can say that the true value of p falls between 27.6 and 32.4 (my SE=2.4).

After plugging the numbers into statcrunch as follows, Mean=.30, SD= .0247, and P(x>.32). The P-value it returned was .2091 after rounding. What does this mean? If all calculations are correct and ceteris paribus, then a P-value this high "fails to reject" the null hypothesis. Ultimately we have insufficient evidence to reject the null and we can conclude that the graduates experiences are not very different than what has been discovered in the population in this particular case.

As always questions, comments, concerns? Hope everyone has a great Fourth of July weekend!!!!