Be careful of the move from data to conclusion! You say "whether one class really is learning the subject better than the other, and by how much?"
Even assuming the test yields a good measure of how well the students know the material (which should be investigated, rather than assumed), it isn't telling you whether students have learned more from the class itself, unless you assume all students started from the same place. As I gather is common in this field, the problem isn't statistics per se, but framing questions that can be answered by the kind of data you can get. >Stan Brown wrote: > >> Another instructor and I gave the same exam to our sections of a >> course. Here's a summary of the results: >> >> Section A: n=20, mean=56.1, median=52.5, standard dev=20.1 >> Section B: n=23 mean=73.0, median=70.0, standard dev=21.6 >> >> Now, they certainly _look_ different. (If it's of any valid I can >> post the 20+23 raw data.) If I treat them as samples of two >> populations -- which I'm not at all sure is valid -- I can compute >> 90% confidence intervals as follows: >> >> Class A: 48.3 < mu < 63.8 >> Class B: 65.4 < mu < 80.9 >> >> As I say, I have major qualms about whether this computation means >> anything. So let me pose my question: given the two sets of results >> shown earlier, _is_ there a valid statistical method to say whether >> one class really is learning the subject better than the other, and >> by how much? ________________________________ Jill Binker Fathom Dynamic Statistics Software KCP Technologies, an affiliate of Key Curriculum Press 1150 65th St Emeryville, CA 94608 1-800-995-MATH (6284) [EMAIL PROTECTED] http://www.keypress.com http://www.keycollege.com __________________________________ ================================================================= Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =================================================================
