The purpose of the project is to give you an opportunity to work on a larger analysis than what we normally tackle in the homeworks, and for you to practice working in a group (each group will have three or four people (or five, with special permission). The main advantage to working in a group is that you can bounce ideas off one another, and hopefully uncover more interesting features of the data. The main problem, as most of you will discover, is co-ordinating time to meet together.
I expect the project to be approximately three times as much as normal homework. I think this is fair: you have almost three times as long, and you can share the work. Don't mistake the effort you put in with the length of the final project - here are a couple of quotes to get you thinking:
"I have made this letter longer than usual, because I lack the time to make it short."
Blaise Pascal
"If I am to speak ten minutes, I need a week for preparation; if fifteen minutes, three days; if half an hour, two days; if an hour, I am ready now."
Woodrow Wilson
In this project, you will perform a complete organisation, selection and summary of a data set. You will practice the skills you learned in class with the Shangri-La diet data. This time you're going to use data on baseball players from the baseball databank.
We have provided a spreadsheet (players.xls) that contains data about each player (when born, height, weight etc) and for some players, how much they were paid each year. We've removed players born before 1904 (because excel can't handle those dates), and people who didn't play (i.e. managers and umpires). If you would like to investigate some other aspect of the data, you can, but you'll need to tidy up the data yourself. This is a good idea if you want to get really good marks!
There are two parts to this project: In the first, you'll work out how and which data you will use. The data available is quite massive, so you will need to first read about what is available, then discuss questions you aim to answer, and identify the data necessary to answer them (try to not use more than four co-variates; also think of ways to reduce the number of rows you're dealing with). In the second part, you'll actually download and manipulate the data, and try and answer your questions using the techniques discussed in class, with pivot tables and graphics.
Here are some questions to think about:
12 Feb. Initial questions and drafts of graphics and tables. This should be a rough draft (the writing doesn't need to be polished or complete), but the basic structure should be there.
I suggest you look through the data individually, then meet as a group and brainstorm things that might be interesting to explore. Devise a strategy collaboratively, and don't forget to come up with a scheme to divide the labour. (You might want to team up with another group to reduce the job even further)
21 Feb. An 8-10 page report organised as described below, and an excel spreadsheet containing your raw table, pivot tables and graphics.
And an individual, one page report on how well your group worked together. What worked well? What didn't work? What will you do differently next time? Include an estimate of how much work each group member did (including yourself).
Overall grade breakdown:
The grading rubric that I'll use is available as a pdf, and is described in more detail below.
The purpose of the introduction is to introduce the data set, provide some context, and guide me as to what to expect from the rest of the report. You may find it easiest to write last, after the rest of the report. It should be about a page in length.
You should have approximately four or five main questions and associated findings, each which may be broken down further in more specific minor questions. Some of these questions will occur to you immediately upon looking at the data, and some will require considerable considerable exploration before they occur to you. To get to the four questions that you report on, I'd expect you to have had 20 or more questions. A lot of the time you will run into a dead end, or the answer to your question will turn out to be uninteresting or obvious. It is always disappointing not to report on something that you spend time working on, but it does make for a better report. You might want to briefly mention some of the dead ends you went down to demonstrate that you've done more than just the obvious.
A good way to present this material is to have one plot or table on a page, along with an accompanying description of what the plot tells you. Don't forget to use headings to break up the sections. You may need multiple plots and tables for each question.
Like your homeworks, I will assess the questions and findings based on the three criteria of curiosity, scepticism and organisation.
In all real data sets you will need to spend a lot of time cleaning up the data - fixing incorrect values, dealing with missing values etc. Don't forget to give a brief description of what you did - that could count as one of your 4-5 questions/findings.
The conclusion should summarise your findings. Rather than just repeating what you've already said, try and weave your findings together into a consistent story. You should also reflect a little on other questions that the exploration raised, and what you would do next. Do you need to collect more data? Or collect data in a different way?
I'll also mark the general presentation of the project. This is divided into three parts: text, tables and graphics. Tables and graphs should follow the guidelines we have discussed in class. If you're struggling with the writing, the writing and media help centre can help. You can also read over your past assignments to find the things that we do and don't like.
Last, but not least, your report should include an (electronic) appendix which allows the reader to reproduce your findings. For this project, this would be a nicely arranged excel file containing (some of) the pivot tables and graphics that you used in the report.
To give you some idea of what a great report looks like, here are some examples from previously classes.