Math 217: Applied Statistical Methods – Winter Term, 2011

 

“The best thing about being a statistician is that you get to play in everyone’s backyard.”

 

“Far better an approximate answer to the right question, which is often vague, than the exact answer to the wrong question, which can always be made precise.”

 

–        John Tukey (1915 – 2000)

 

Course Goals

In general, a statistics course teaches you to both descriptively and inferentially explain (read: model) the variation that occurs in real data. Upon completion of this course, you should know how to (among other things)

·         Graphically and numerically describe single variables and relationships between variables in a data set

·         Via regression, model linear relationships between multiple variables, make inference about the relationship in the population (based on the sample), and diagnose the model to ensure it is trustworthy

·         Understand experimental design and analyze standard experimental designs via one-variable and two-variable analysis of variance

·         Analyze categorical data via two-way tables, inferential procedures, and logistic regression

·         Use bootstrapping to find the sampling distributions of statistics for which we don’t have mathematical theory and understand the idea of permutation tests

  • Understand and apply the general concept of modeling and inference, as well as its limitations (including all conditions that must be met)
  • Serve capably as a statistical consultant, asking important questions, gathering appropriate information, and following-up with additional questions

 

Contact Information

Professor: Joy Jordan

Office:   410 Briggs Hall

Phone:   832-6894

E-mail:  joy.jordan@lawrence.edu

Web page:  www.lawrence.edu/fast/jordanj/

 

Please note the URL for my homepage. On this page is a link to the Math 217 web page, where I will post homework assignments, handouts, etc. You should visit this website regularly. Also note I check email fairly regularly throughout the day (typically 3 times), but if you have an emergency or a message that is urgent, then you should definitely call, not email.

 

Required Textbook

Stat2: A Second Course in Undergraduate Statistics, Cannon, etal, W.H. Freeman and Company, 2010

We will class test this textbook, written by close colleagues of mine. Good news: you get free copies! It’s possible you’ll find a few typos or explanations/problems that aren’t clear. Please mark up your book, not only for your own learning, but to give feedback to the publisher (you are an important part of this textbook-creation process). That said, this textbook is an excellent, thoughtful resource—read it carefully and soak in its ideas.

 

Office Hours

Monday: 3:00 – 4:30, Tuesday: 2:30 –3:30, Wednesday: 11:30 – 12:25, Thursday: 1:30 – 3:00

 

If these times do not work with your particular class schedule, I am happy to make individual appointments for other times. (You need not make an appointment during regular office hours—just come in.) Please ask if you need help, and I will do my best to assist you. That said, I am but a guide and you are the actual owner of your education. I expect you to come to office hours prepared (e.g., having done the reading, asking specification questions about homework problems—that is, asking for guidance, not for answers). Besides office hours, anytime my door is open, feel free to come in and ask questions. If my door is closed, I am either out of the office, or I’m working and prefer not to be disturbed.

 

 

Homework

You will turn in regular homework assignments (“by hand” problems; computer-aided analyses; partial report write-ups); these problems will be graded. Your grade will depend on both the content and exposition of your answers (write out the solutions carefully). You can talk with other students when you initially think about the problems, but you must write-up your solutions completely on your own. (For example, if you work as a group and one student writes a solution on a white board, then other students can look at the answer and discuss the ideas, but cannot simply copy the solution word-for-word from the board.) When you sign the honor code on each assignment, you are attesting that your written solutions are in your own words.

 

Class Participation/Discussion/Mini-Presentations

Class participation is an integral part of this course and it will be assessed (see final-grade weighting below). Because there are so few students in the course, we will meet “seminar style.” That is, the course will be student-centered (e.g., your questions, mini-presentations, explanations), not teacher-centered (e.g., very few standard lectures). This puts more responsibility on you, but it also means you will own this material. And I will dive in and participate right along with you. We’re in this together! I haven’t included a course schedule; we’ll let our discussions and your inquiry guide our coverage. Hence, we all must stay flexible. That said, you will be expected to do work (e.g., careful reading, presentation of problem solutions, summary of information, preparation of questions) for every class period.

 

Project

Beyond the standard homework problems, I want you to analyze a rich data set and carefully write your analysis in report-form. Depending on the material we cover (read: if we get to logistic regression), this experience will be a project based on Lawrence admissions data. An important part of becoming a practicing statistician is to learn the art and skill of consulting (working with a client in a different field and assisting with the analysis of the client’s data). If the timing works, you will consult with Ken Anselment, Director of Admissions. If the timing doesn’t work, then you’ll engage with some other large data set and do a thorough and appropriate analysis. (The project will come in the last few weeks of the term—we’ll reassess once we get there.)

 

Computer Lab (Time To Be Determined, Briggs 421)

In the weekly computer lab, we’ll investigate and interpret real data (using statistical software, Minitab and R). Although the computer will do most of the calculations, we will grapple with the important steps of selecting the correct analysis, checking any conditions of the analysis, and interpreting the results. These are subtle, yet vitally important skills for a statistician.

 

Grading

Your final grade is based on a weighting of homework assignments (55%), class participation (20%), and project (25%). The percentages might change, depending on the extent of the project (stay tuned). The letter grades will be assigned as follows, corresponding to Lawrence’s GPA system (note: the cutoff is the lowest percentage that receives that letter grade):

 

Cutoff

Grade

93.75

A

90.00

A-

86.25

B+

83.75

B

80.00

B-

76.25

C+

73.75

C

70.00

C-

66.25

D+

63.75

D

60.00

D-

 

Life Balance

Because I love statistics so much, I will encourage you to work hard to learn the material. But please realize your self-worth is not associated with your letter grade on a particular homework assignment or presentation (or even with your final course grade). You are all good people, regardless of your official class performance on tasks. (This doesn’t mean I won’t have expectations on how hard you work, but I certainly won’t judge you personally if those expectations aren’t met.) Furthermore, I think as a society in general, and at Lawrence in particular, we are over-scheduled and allow precious little downtime and quiet reflection. I encourage you to think carefully about the intensity and number of courses, activities, and obligations in your life, and to seek balance as much as possible. (I’m happy to talk with you more about this—that is, we can discuss life as well as statistics.)