This handout is also available in PDF.
Welcome to one of the Spring 2008 sessions of Grinnell College's MAT/SST 115 Introduction to Statistics, which is described relatively briefly in the official blurb. My own take on the course is that we will be working on making you quantitatively literate: You should leave the course (a) able to think critically about reports that include a quantiative component and (b) able to design your own analyses and experiments to understand large data sets. That is, you should be an informed consumer and producer of quantitative information. Kent McClelland provides a more detailed analysis of these learning objectives. In addition, as we also be working on your general thinking and work skills, as all Grinnell classes do.
This semester, all three sections of the course are following the workshop model. Longstanding evidence in science education suggests that students learn better and more if they participate actively in working on problems than if they primarily listen to lecture and do problems separately. This means that each day in class, you will come in and work on a series of problems, most frequently with one or more partners.
In this section of MAT/SST 115, we are also taking a different approach to statistical software. Rather than the commercial software, Minitab, we will be using an open-source statistical package, R. Details on that software are available elsewhere in this Web site, as are my reasons for using R.
In an attempt to provide up-to-date information, and to spare a few
trees, I am making this as much of a
paperless course as I can.
Hence, materials will be in a course web. If you are puzzled by the
organization of the Course Web, you may want to read the basic instructions for using this
course web. If you find that you want paper copies of pages, please
read the notes on printing copies. If you find
that you are regularly printing pages, let me know and I can provide
them for you.
Warning! To succeed in a workshop-style course, you need to participate actively in your own education. (After all, that's part of the point of workshop-style courses.) If you are not prepared to participate actively, please drop this class and take a section next year that is offered in a more traditional style.
Warning! We'll be using computers a lot in this class. Computers are sentient, stupid, and malicious. When things go wrong, don't blame yourself. Ask me, a tutor, or the class mentor for help.
Warning! We are using some cutting-edge software, which means that things will occasionally crash for no good reason.
Meets: MTWF 1:00-2:05, Science 3819
Instructor: Samuel A. Rebelsky (firstname.lastname@example.org), Science 3824. 269-4410 (office). 236-7445 (home). Office hours MTuWF 10:00-11:00, Tu 1:15-2:05, MF 2:15-3:00. I am also available at other times by appointment. I also tend to follow an open door policy: Feel free to stop by when my door is open.
Co-Instructor: Katherine McClelland, (email@example.com), Science 2012A. 269-3060.
Class Mentor: Cassie Sims (firstname.lastname@example.org). Office hours Sunday, Tuesday, Thursday, 9-10 p.m.
Class Grader: Eric Davenport
Grading (subject to change):
I will drop your lowest homework grade.
Extra Credit: I will often offer 1/2 point of extra credit for attending a particular talk (e.g., a computer science talk or college convocation) or for supporting your classmates in their public endeavors (e.g., attending a concert or a dance recital). Each category is capped at 1.5 points. Throughout the term, I may suggest other forms of extra credit.
Tutoring: The Math Lab provides tutoring for 115. Your class mentor will also provide some particular hours. Note that the Math Lab statistics tutors will be better equipped to help you with general statistics issues than with specific questions on the R software.
Rossman, Allan J. and Beth L. Chance. (2008). Workshop Statistics: Discovery with Data. Third Edition. Emeryville, CA: Key College Publishing
The primary book for the class. This text contains both explanations of statistical concepts and a series of exercises to help you learn these concepts.
Your Name Here. (2008). Laboratory Notebook.
In addition to the textbook, you will need a laboratory notebook in which you will record your answers to problems. The textbook also provides spaces in which to record your answers to problems. However, if you write in the textbook, it will be difficult for you to resell it or to share it with a colleague. More importantly, we will occasionally ask you to turn in your work from the book, and it will be easier to provide us with a lab note book than with your book. You need not use one of the fancy lab notebooks for this class: you can use any bound notebook you deem appropriate, including a spiral-bound notebook.
Rebelsky, Samuel A. (2008). MAT/SST 115.03 2008S Course Web. Online
resource available at
The course web, which will contain all the handouts you need for the class, as well as additional useful information.
Success in a workshop-style class, like success in any class, requires effort on your part. To be successful, you must do a variety of things.
Most of these pages are designed for viewing onscreen. If you'd like
to print them, you may want to use PDF versions, which are designed
for paper. Many pages have links directly to the PDF version. If there
isn't such a link, simply replace the
html at the end of
the URL with
I usually create these pages
on the fly, which means that I rarely
proofread them and they may contain bad grammar and incorrect details.
It also means that I tend to update them regularly (see the history for
more details). Feel free to contact me with any suggestions for changes.
This document was generated by
Siteweaver on Sun May 4 08:49:34 2008.
The source to the document was last modified on Sun May 4 08:49:32 2008.
This document may be found at
You may wish to validate this document's HTML ; ;Samuel A. Rebelsky, email@example.com
http://creativecommons.org/licenses/by-nc/2.5/or send a letter to Creative Commons, 543 Howard Street, 5th Floor, San Francisco, California, 94105, USA.