Currently browsing posts filed under "STAT 10/ECON 18"
Here (pdf) are the evaluations from the students in my Winter Study course. I am pleased with the results. The College also distributes to all instructors the same data for the 600 students who filled out the form. I asked for permission to post this summary data but was denied. That seems silly since there is nothing embarrassing in there, but I don’t post such documents without permission, so readers who care are out of luck.
I also think that the College should make public the student evaluations for all Winter Study classes. First, the more information that Williams provides to students, the better the choices they will make. Students who don’t want to work 20+ hours per week should not take a class with that sort of workload. Second, to the extent that certain instructors are doing a poor job, the more people — especially faculty — who know about, the more likely that the problem will be fixed.
What is the argument for not making these student survey results public, at least for Winter Study classes?
A anonymous Williams professor asked me about 300 level courses. Some students take a lot. Some take few. What does the data show?
Excellent question! My class played around with this topic on Friday. (I am always eager to answer questions from Williams professors.) Thanks to the Registrar for providing us with the data. Alas, I don’t have permission to publicly share the data, so, if you have other questions, please ask them in the comments. Basic answer:
See below for more discussion and another chart.
Interested in applied statistics? Come listen to my students’ presentation of their Winter Study project!
Monday January 25, 2009
Quantitative Equity Research: A Winter Study Project
11:00 a.m., Schapiro Hall 241
Andrew Liu ’11 and Nai Chien Yeat ’13 will present their paper “The 52-week High and Momentum Investing — A Replication of George and Hwang (2009).” This work was completed for SPEC 29: Applied Data Analysis. Recommended for those interested in how quantitative portfolio managers conduct research and make decisions.
A good time is guaranteed for all!
Here is the latest work from my class on the ages of the Williams faculty.
Who is the oldest member of the 2009-2010 Williams faculty? Excellent question. Needless to say, the College won’t (and probably can’t) release the ages of individual faculty, but my Winters Study class has progressed from last week to this:
Admittedly, this graphic is sort of ugly, but we are only one week into the class! Further discussion and code for replication below.
In the spirit of transparency, here are some notes on my Winter Study.
1) We have an e-mail list for the class. But guests are welcome! Let me know if you want to sign up.
2) We started the class with 6 people. One student dropped for a good reason but two others dropped for the wrong reasons. The remaining three are ready to work hard, I hope!
3) Here is the graphic that we created in the first class.
Pretty cool, eh? See the code below for details and reasoning. Any R users out there willing to try to replicate our work? That would be cool.
Readers (with a Williams ID) interested in my Winter Study class can check out the Glow page for the class here. (Glow is the in-process replacement for Blackboard and is based on Moodle. It provide a lot of interesting features, but there will be lots of initial problems as Williams, the students and I get used to it.)
Here (pdf) is the latest version of the syllabus. It is too late (obviously) for me to make major changes for this year, but I plan on teaching a class like this, either at Williams or elsewhere, for years to come, so feedback is always appreciated. Also, if anyone has access to interesting Williams-related data sets and would be willing to let my students use that data for their projects, please let me know.
Of the 2,000 students at Williams, at least 40 (call it 2%) would be better off if they took my Winter Study class, SPEC 29: Applied Data Analysis, then if they took a different class. I will teach them enough pre-professional quality data analysis skills that they will be able to get a better internship/job (and then do better in that position) then they would have if they had not taken the class. Consider what students from last year accomplished.
Read below to figure out if you are in that 2%.
A report about my Winter Study class from last January.
1) I taught ECON 18: Quantitative Equity Research last January. Here are prior posts on the class at EphBlog. Here is a webpage with students papers, my comments and so on. Teaching was great fun! If you ever have the opportunity to teach at Williams, you should do so.
2) I practiced in the class what I have preached for many years at EphBlog.
First, I required that the students post their final papers for all to read. The more public that student work is, the more care they will put into that work and the better that work will be. Williams professors often whine about the lack of effort that students put into their Williams essays. This (real!) problem has a simple solution. Post the work on-line. We have seen some examples of this (here and here) at Williams. Can readers point to others?
Second, I posted my own comments to the papers on-line as well. The more public that professor work is, the more care they will put into that work and the better that work will be. Williams students often whine about the lack of effort that professors put into their written comments. This (real!) problem has a simple solution. Post the comments on-line. Is there a single Williams professor (besides me!) that does this?
The more public and open the College makes the process and product of academic work at Williams, the better that work will be done. Want to increase the quality of intellectual life among current undergraduates? Let the rest of us listen in.
Third, I taught the students to make their work reproducible as all good research is. (See background on the Replication Standard.) With access to the underlying data (which I can provide) anyone can reproduce their results because they provide the computer code from which the papers (including tables and figures) are generated. (Do we have any R users who would like to give this a shot? E-mail me!)
3) Seven students showed up for the first day but three dropped out. One left because she wanted to enjoy her senior Winter Study and she already had a job in private equity lined up. Another student had a hand injury and was worried about all the coding/typing involved. Both drops were reasonable.
4) My biggest mistake in teaching the class was assuming that I could scare the students into doing a lot of work in the first 10 days of Winter Study. I indicated (correctly!) that it would require 100 hours of work to learn all the material that we needed to learn — mainly how to use the various computer tools: R, Emacs, Sweave and so on. I told them that I would not hesitate to fail anyone who did not do the work. I tried to (credibly?) play the bad guy.
Alas, I was not successful, either because students saw through me or they called my bluff or they just didn’t give the matter a lot of thought. I told them to, for example, read an “Introduction to R” and do all the exercises. And they (or at least most of them) just ignored me. Frustrating! But the fault lies into my naivete about student preferences and planning. I won’t make the same mistake this year when I teach Applied Data Analysis. (More on that class later in the week.)
5) But, despite the slow start, I think that the students all worked hard and accomplished quite a bit. Read their papers. I am certain (corrections welcome!) that their work is much higher quality than most of the papers submitted for Winter Study credit and that it is probably better than almost all the empirical work submitted in upper level ECON classes. Indeed, my guess would be that it is every bit as substantive as the data analysis done for most senior theses in economics.
6) I let/required the students to work in two pairs. I also allowed the two groups to share code and discuss approaches. (You can see a great deal of commonality in the functions that they use.) This is a good thing in that learning to work with your peers on joint projects is a valuable skill. But it is a bad thing because the weaker students will tend to just sit back and let the stronger students figure everything out. If I can use student X’s code for solving a certain problem, why don’t I just let him figure it out rather than beating my head against the wall?
I hope to solve this problem this coming January by requiring more individual work at the beginning while still allowing/requiring joint work on the final projects.
7) One student was clearly the star of the class, accomplishing (as best I could tell) more than 2/3’s of the total programming work. I tried to give this student extra positive feedback, both while this was going on and after the class was over. I let him know that I would be eager to provide him with a recommendation letter.
And that turned into a happy story! He was a senior, interested in a variety of possible careers paths and options but not committed strongly to any one of them. I served as a reference for a few jobs that he was applying to but also let him know about a finance summer job at a quant hedge fund that, with luck, might turn into a full time job. He expressed an interest, I helped get him an interview (I have helped place a couple of other Ephs at this firm) and his own brains got him the job. He has done well and the firm made him a full-time offer. Whether or not he will (or should) stay in finance is hard to say, but it is always nice to have options.
Now, partly this story celebrates his achievement as well as providing an excuse for my own bragging. But the central lesson for all current students is the same as always: If you want to maximize the opportunities that you have after graduation, the more networking that you do, the better — whether in the specific context of a Winter Study class or in general work of Williams alumni.
8) I have no doubt that, measured by my own goals, the class was a success.
If you had tried to conduct a similar piece of financial research before taking this class, you would have done X well. Now that you have taken the class, you will do Y well, both with your actual paper and with any future financial research you choose to undertake. The success (or failure) of the class can be measured by comparing Y with X.
For all 4 students, Y is bigger than X. Yet the central problem with the class was that Y was not as big as it could have been. I will try to learn from my mistakes and do better in January.
9) If anyone has any questions about the class or suggestions for what I might do next time, please write a comment.
Looking to get a job post graduation? According to the New York Times, you should take David’s Winter Study Course. Students taking this class are much more likely to get desirable internships/jobs than students, all else equal, who do not take this class.
Chad Orzel ’93 on Dreadful Graphics and Health Care Costs. After showing how to improve a graphic originally from a right-wing think tank, Orzel writes:
It doesn’t change the content in any way (and the significance of this comparison remains somewhat dubious), but at least it doesn’t look like it was made by a chimpanzee with Excel. Honestly, it’s no surprise that our political discourse is so hopelessly superficial, given the godawful way the people conducting the debate stumble around presenting information.
If this were coming from a first-year college student, I would agree [that excessive criticism is rude]. This graph was produced by somebody at the American Enterprise Institute, which is ostensibly an intellectual operation staffed by people who ought to know something about how to deal with numerical data.
Indeed. But the real lesson for current students is that there is a significant unmet demand, on both the right and the left, for people who can create useful graphics. There are thousands of smart college graduates who want to work in politics and policy. Almost all of them can write and think. Want an advantage over them? Learn some basic graphics and statistics. That will increase your chances of getting the entry-level job at the American Enterprise Institute (right) or the Center for American Progress (left).
How? Either follow my advice about course selection or take my 2010 Winter Study class: SPEC 10: Applied Data Analysis or both.
I will be teaching STAT 10 Applied Data Analysis during Winter Study 2010. It is the successor course to ECON 18 from last January. Below is the draft of my course description. Although I am just as happy to teach this class with 4 as with 40 students, I think that several dozen students would be better off taking my class than taking some of the weaker (but still serious) course offerings. [Which is not to say that the typical student would be better off in my class than in something unusual and/or travel-related.]
Anyway, how should I reword this to make more students (who would benefit) more likely to sign up?
For those interested, here is the final version of the syllabus for ECON 18: Applied Equity Analysis, my Winter Study class. Auditors and visitors are welcome! Our next meeting is in Hopkins 108 on Monday at 9:00 AM. I maintain an e-mail list for the class on which we discuss various programming issues. Let me know if you want to sign up. The final projects will be posted at the end of the month.
For those thinking of teaching at Winter Study, I highly recommend it.
Registration is now open for Winter Study classes. Here is a very rough draft of my syllabus for ECON 18. Comments and questions welcome! Apologies for the formatting and sloppiness, but I wanted to get something out there for interested students to consider. What is the over/under on how many students will sign up? I’ll go with 10, but hope for 20.
My Winter Study class, ECON 18: Quantitative Equity Research, is now in the course catalog. Oo-ra! I am looking forward to this. See the link and previous discussions for more details. A few comments.
1) My teaching assistant has recommended that I change the title. He thinks that the course sounds too boring/hard and is concerned that no one will sign up. Is he right? Comments welcome. I don’t want a lot of students to sign up, but I do want to teach the course so I need at least 8. My thinking is that there are at least 8 students who want a serious introduction to quantitative research and/or some insight into life on Wall Street. Am I wrong?
2) The course has no prerequisites, but I urge any interested students to take STAT 201 this fall. See also my advice on course selection for a finance/business career. We will be using R and working with large amounts of financial data. Here is an introduction (pdf) that I use, although only R and Sweave will be required for the course.
3) I hope to have a syllabus available later this month, before students need to make their course selections. I will be making all course material available on the web. Transparency rules and feedback is welcome.
Interested in taking my Winter Study class on Quantitative Equity Research this January? Read below.
He might be victimized by the plague of intolerance and harassment against junior lecturers.
Currently browsing posts filed under "STAT 10/ECON 18"