STA 302 H1F / 1001 HF – METHODS OF DATA ANALYSIS IFall 2011Lectures: Tuesdays 10:10–11:00 in OI G162 (no lecture on Tuesday, November 8 (Fall Break))Thursdays 10:10-12:00 in OI G162Tutorials: Tuesdays 11:10–12:00 in OI G162During most tutorials, a teaching assistant will be available to answer questions.Tests and assignments will be returned in this hour.This hour may occasionally be used for lecture. Announcements will be made in advance.Instructor: Dr. Alison GibbsE-mail: [email protected]: SS 5016ATelephone: (416) 946-7589Office hours: Thursdays 12:10–14:00 (priority to STA 302/1001 students)Mondays 11:10–13:00 (priority to STA 220 students)Appointments for other times can be made by e-mail.More office hours will be scheduled before tests and assignment due dates.Tutorial teachingassistant: Andriy DerkachCourse Announcements and a discussion board are available through https://portal.utoronto.caweb pages: Lecture notes, SAS examples, practice problems, assignments and previous exams are athttp://www.utstat.utoronto.ca/alisong/Teaching/1112/Sta302/sta302.htmlCourse contentThis course covers how to analyse data when regression models are appropriate. Althoughthe focus is on the methodology of data analysis, some underlying theory will also bedeveloped. Topics to be covered include: initial examination of data, correlation, simpleand multiple regression models using least squares, inference for regression parameters fornormally distributed errors, confidence and prediction intervals, diagnostics and remedialmeasures when the model assumptions are violated, interactions and dummy variables,model selection, least squares estimation and inference for non-linear regression.1Pre-requisitesStudents should have a second year statistics course such as STA 248H1 / STA 255H1 /STA 261H1 / ECO 227Y. Students are expected to also have the mathematics pre- andco-requisites required by students in these second-year statistics courses. You will needto know basic matrix operations. A review of matrix algebra is available on the textbookwebsite at http://www.stat.tamu.edu/~sheather/book/tutorials.php.Follow-up coursesSTA 303H1 (Methods of Data Analysis II) focusses on aspects of linear models that arenot covered in STA 302H1 such as non-normal and correlated response variables. Mostapplied courses in the Statistics Department require STA 302H1 as a pre-requisite.TextbookThe textbook is A Modern Approach to Regression with R by Simon J. Sheather. We willbe covering most of chapters 1 through 7. Topics in later chapters will be covered in STA303H1. The book is available to purchase and is also available as an e-Book through theUniversity of Toronto library website.Datasets and other resources are available at the textbook websitehttp://www.stat.tamu.edu/~sheather/book/.Another good reference for the course material is Applied Linear Regression Models, 4thedition by Kutner, Nachtsheim, and Neter. A copy of this book is on reserve at theMathematical Sciences Library.Course web siteThe course web sitehttp://www.utstat.utoronto.ca/alisong/Teaching/1112/Sta302/sta302.html willbe used to post lecture notes, practice problems, SAS examples used in lecture, assign-ments, and previous exams. It is recommended that you print copies of the SAS examplesto bring to lecture. The lecture on Tuesday, September 20 will be an introduction to SAS.There will be notes posted on the web site that you may wish to print and bring to thislecture. When looking at previous exams, resist the temptation to look at the solutionsuntil you have tried the questions and spent at least a day thinking about solutions toproblems of which you are unsure.Blackboard will be used for announcements. You are also encouraged to use the discussionboard on Blackboard.Accessibility NeedsThe University of Toronto is committed to accessibility. If you require accommodations fora disability, or have any accessibility concerns about the course, the classroom, or coursematerials, please contact Accessibility Services as soon as possible:[email protected] or http://studentlife.utoronto.ca/accessibility.2CommunicationIn general, I am not able to answer questions about the course material by e-mail. Beforeyou send an e-mail, make sure that you are not asking for information that is already onthe course web site, or questions about the course material or assignments that are moreappropriately discussed in tutorial or during office hours. If you do not get a response,this may be why. Questions about the course material can be posted on the discussionboard on Blackboard. I will check it at least once every 2 days.E-mail is appropriate for private communication. Use your utoronto.ca account to ensurethat your message doesn’t automatically go to my Junk folder. I will generally answer e-mail within one business day.Announcements will be posted on Blackboard. Please check there regularly. If an urgentmatter arises, I may contact the entire class by e-mail. In order to receive these messages,please make sure that your ROSI account has your utoronto.ca e-mail.EvaluationWeight Date Time LocationTerm Test 24% Thursday, October 20 10:10-11:40 a.m. TBAAssignment 1 7% Tuesday, October 11 due at 12:00Assignment 2 7% Thursday, November 10 due at 12:00Assignment 3 7% Tuesday, November 29 due at 12:00Exam 55% scheduled by FacultyIf your exam mark is better than your test mark, the exam weight will be 67% and thetest weight will be 12%.The test will be written in a room other than the lecture room (location to be announced).Practice problems will be posted on the web for each chapter. The practice problems areto help you prepare for the tests and exam and are not to be handed in. The assignmentswill each be a data analysis project for which you will use SAS. You will not need to knowSAS syntax on the tests and exam, but you will need to interpret output from SAS.If the test is missed for a valid reason, you must provide appropriate documentation, suchas the University of Toronto Medical Certificate, University of Toronto Health ServicesForm, or College Registrar’s Letter. You must submit this documentation within oneweek of the test. If documentation is not received in time, your test mark will be zero. Ifa test is missed for a valid reason, its weight will be shifted to the final exam.No late assignments will be accepted without documentation of a valid reason.Any requests to have marked work re-evaluated must be made in