Question 1181648
Type II errors are errors of omission where one accepts a false null hypothesis.
Here, Ho is mean SI score is 85 or higher
Ha is the mean SI score is lower.
If one rejects Ho, a type I error is saying the the score is lower when it really is the same or even higher. One is overcalling an error.
If one accepts a false Ho, the conclusion is the score is higher when it isn't. One is missing the error. 
So the error is accepting the null hypothesis that the mean is the same (or higher) when the mean is lower.
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Rejecting Ho will either be correct or lead to a Type I error.
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Yes, you can do this in Excel. I like the TI-83 a lot better at least for checking the calculations if not for outright doing them.
Here, the calculation will be z=(79-85)/(10/sqrt(n), and compare that to the critical value z that is chosen.
This doesn't need to be done in Excel, unlike tables (Chi-Square), large data sets for mean and sd, analysis of variance.

Most of what you will be doing is dealing with Type I error. Power to show a difference when it really exists has to do with Type II error, which often occurs when the sample size is too small to show a true difference, and one fails to reject when one should.