I know a number of you are using Excel to do the number crunching for this course. Some of your learning processes involve working through the step-by-step equations using some or many of Excel’s built-in stats functions along with some formulas. This is a good process for many folks.
However, that process can be time-consuming. Another approach is to use the free Excel Data Analysis Tool Pak which has some of the solution processes we need in this course. However, they are not as flexible as we need in that many of them require raw data while many of our problems in MSL give us summary data. In the real world, you are not likely to get summarized data, so this approach works for most business needs. But not so much here in an academic setting. If you do not see the analytics tab when you click on the Data tab in the main ribbon, you need to activate the toolpak. Email me and I will send a procedure to do that.
I have found a Pearson product called PHStat that is an Excel add-in that is better suited for our needs in this course. Given you have a Pearson ID/PW to get into MtStatLab, my understanding is that some of those will work to get you into the Pearson website where you can download PHStat. http://wps.aw.com/phstat/ If you do not have a Pearson ID that works, you can register and pay $10.00 to buy access to the website and to PHStat. I assure you it is well worth $10 for the time it will save you. It is not perfect, e.g. some of the two-sample tests include an option to get the confidence interval while others do not, but overall it is a bargain.
And again, I have no stock in Pearson or StatCrunch/PHStat or anything against basic Excel. Indeed, many of you will find you need Excel skills in future Excelsior courses and in your future business life. Using PHStat and StatCrunch in conjunction with Excel will make your life easier in this course and in future quantitative courses. I just believe strongly that the real goal of this course ought to be to produce people/managers who understand what questions can be asked of data, how to use technology to crunch the numbers, how to interpret the results, and, importantly, how to communicate the business implications of those results.