Math 215 Introduction to Statistics
Course Information and Syllabus

Instructor

Bob Dobrow    Office: CMC 218     Phone: 646-5633
E-mail:  rdobrow@carleton.edu     Homepage:  http://www.people.carleton.edu/~rdobrow/
Office hours
     Mon 2-3 pm
     Tues 1-3 pm
     Wed 11 am-Noon
     Thur 1:45-2:45 pm

Welcome to Statistics! The focus of this course is on data: understanding data, presenting data, producing data, and using data to solve problems. This term we'll talk about: airfares, baseball, the census, clinical trials, the death penalty, discrimination suits, exit polls, Iraq war casualties, lotteries, murder trials, and TV game shows. Statistics touches all these areas and countless more. Statistics are everywhere, and statistical methods are becoming ever more important throughout the natural and social sciences. You will study the main ideas and methods of statistics by exploring real data and applications.

The texts are Intro Stats, 2nd edition, by Richard D. De Veaux, Paul F. Velleman,and David E. Bock (make sure you have the right edition!); and the lab manual Statistics Labs with S-PLUS, 2007-2008. You will need a calculator. Please bring your textbook and calculator to every class.

Your course grade will be based on a weighted average of (i) class participation, (ii) homework, (iii) one paper, (iv) three midterms, and (v) a final data analysis project, using the following weights:

Class Participation	4%
Homework	15%
Paper	9%
Midterms (3)	54% (18% each)
Final Project	18%

You are expected to attend class regularly and participate in the discussion as best you can. While we will be covering much of the material in the textbook, there will often be times when I present material that is not in the book. In addition there will be in-class work, demonstrations and activities not covered in the book. You are ultimately responsible for what takes place in class. If you cannot attend a class let me know as soon as possible.

Homework will be assigned after every class period. Some of these problems will be odd-numbered exercises from the textbook, with solutions in the back of the book so that you can check your work. A few problems will be designated to be handed in for grading. For these problems, your solutions must be neat, clear and well written You must show your work and give your solutions in context. Homework problems will require some explanation and interpretation of numerical results. Remember that data have context, which should be made explicit.

Doing problems on your own (in addition to reading and thinking) is the main way that you have for learning the material. And generally the more problems you do, the better prepared you will be.

Homework should be handed in at the beginning of class. Use smooth-edged paper (not ripped out of a spiral notebook), put your name on each page, and staple pages together. Put care into your work. If you have very poor penmanship then type your homework. Work that is sloppy and not legible will not be graded. Late homework will not be accepted under any circumstance (including illness). But in computing your final homework grade I will delete your three lowest homework scores.

The class will meet occasionally in the Statisics Computer Lab in CMC 201 (see schedule below). Please bring your lab manual and textbook to those classes. For homework assigned from lab work, see the Guidelines for Lab Reports for how to prepare these labs.

There will be three mid-term exams. Exams will be in class and closed book, and you will need your calculator. See the schedule below for exam dates.

For the final data analysis project you will bring together many of the ideas and topics from throughout the term. You will: (i) generate your own question of interest, (ii) produce your own data, (iii) use appropriate statistical methods to analyze the data, and (iv) report on your results in a paper and in an oral presentation. This will be a group project, and groups of three will be assigned after midterm break. The group talks (and end of class festivities) will take place on Saturday, June 7, and Monday, June 9, 3:30-6 pm. The final paper will be due by Monday, June 9 at 3:30 pm.

Syllabus and Schedule

Class	Date	Events and Topics
1	Mon 3/31	Introduction
2	Wed 4/2	Data and Graphs
3	Fri 4/4	Graphs and numerical summaries
4	Mon 4/7	Class in Lab
5	Wed 4/9	Standard deviation and normal model
6	Fri 4/11	Association and Correlation
7	Mon 4/14	Regression I
8	Wed 4/16	Regression II Class in Lab
9	Fri 4/18	Randomness
10	Mon 4/21	Test 1
11	Wed 4/23	Surveys and Sampling
12	Fri 4/25	Experiments and Observational Studies
13	Mon 4/28	Probability I
14	Wed 4/30	Probability II
15	Fri 5/2	Probability III
Midterm Break
16	Wed 5/7	Sampling distributions
17	Fri 5/9	Test 2
18	Mon 5/12	Confidence Intervals
19	Wed 5/14	Hypothesis Tests I
20	Fri 5/16	Hypothesis Tests II
21	Mon 5/19	Error and Power
22	Wed 5/21	Two samples
23	Fri 5/23	Inference about means
24	Mon 5/26	Class in Lab
25	Wed 5/28	Topics in inference Class in Lab
26	Fri 5/30	Topics in inference
27	Mon 6/2	Test 3
28	Wed 6/4	Topics in inference
	Saturday 6/7 and Monday 6/9 3:30-6:00 pm	Final Project presentations

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