The Bootstrap Method The bootstrap method is a very useful tool to have an introductory statistics class. The bootstrap method begins with a sample of size n. Then a large number (I use 10,000 in my classes) of samples of size n are drawn with replacement from that sample. A sample statistic is computed for each sample. A typical use of bootstrapping involves the mean, but this procedure can be applied to the median, quartiles, variance, … Percentiles can be…
I have had a few questions about how I am managing to work all of these early inferential projects into my Intro Stats course. 1) Switching from Chapter Exams to a Midterm and a Final In the first 7 chapters of our textbook I used to give 4 exams. That means that I would use 4 days for exams and approximately 6 days for review. I have 4 days built into my calendar for review (2 days) and the midterm…
This week I began with a bootstrap project for a paired-difference/matched-pairs scenario. Download a pdf of the Project Here One of my goals is to get students working with data they have collected, so I had students collect prices for 25 identical items at two stores. We used this for one of the investigations. Investigation 1 A researched was investigating whether sons are taller than their fathers. My students were provided with 13 matched pairs. I had them find the…
Last week we did our third project that focuses on introducing inferential statistics earlier in the semester. Download the Activity (pdf) Here The bootstrap method repeatedly samples from a sample (with replacement) to help develop an interval estimate of any population parameter. For example, if there is a sample of 10 numerical values we select 10 values (with replacement) and compute the mean of that sample. We then repeat that process for a total of 1000 samples. We can then…