Statistics is the science and art of obtaining, analyzing and interpreting data and provides a set of essential tools that assist researchers in almost all disciplines. This course will prepare students to solve basic problems encountered in research and to make sound data-based decisions. All methodologies discussed in this course will be approached in a manner rigorous enough to permit students to apply them at a level sufficient for publication in scientific journals. Statistical computing will be carried out using JMP 8.0, a SAS product.
| Instructor: | Professor Rob Strawderman 1172 Comstock Hall rls54@cornell.edu Office hours: Wed, 1:45-2:45, Comstock 1181 |
| Class: | MWF 12:20PM - 01:10PM, IVS 305 |
| Textbook: | A First Course in Statistical Methods
(FCSM; 2004), Ott & Longnecker ISBN-10: 0534408060, ISBN-13: 9780534408060 Data sets for the text book are available online. |
| Prerequisite: | Graduate standing or permission of instructor. If you are interested
in auditing this course, please contact Bea Johnson(bj11@cornell.edu)
before you enroll. |
| TAs: | Head TA: Haim Bar <hyb2@cornell.edu>, office hours: Tuesday, Thursday, 11:00am Other TA's: Cecilia Earls <ceciliaearls@hotmail.com> (office hours: Thursday, 1:15pm) Lynn Johnson <lms86@cornell.edu> (office hours: Friday, 10:00am) Rajendran Narayanan <rn63@cornell.edu> (office hours: Thursday, 3:00pm) Matthias Kormaksson <mk375@cornell.edu> (office hours: Wednesday, 2:45pm) |
| Course format: | 3 lectures, 1 lab per week. All lectures will use powerpoint;
slides will be available for download prior to class. All labs and
homework assignments will be distributed electronically. Students
are expected to attend all lectures and labs.
|
| Web site: | We will be using blackboard to post lecture notes, homeworks, solutions,
etc. To access the course web site, simply go to
http://blackboard.cornell.edu and log in using your Net ID.
Then, click on the "All Blackboard Courses" tab, and in the "Course Search"
box, enter STATISTICAL METHODS I, and click "enroll" to add the one with
course ID BTRY6010-Strawderman-Fall2009 to your course list.
Be sure to check the web site regularly for announcements. |
| Labs: | 401 M 07:30PM - 08:45PM, MNL B30A, Cecilia Earls 402 T 08:40AM - 09:55AM, MNL B30A, Lynn Johnson 403 T 02:55PM - 04:10PM, MNL B30A, Rajendran Narayanan 404 M 03:00PM - 04:15PM, MNL B30A, Matthias Kormaksson |
| Software: | JMP 8 |
| Grading: |
Homework = 150 points Prelims (300 points each) = 600 points Final = 250 points Total = 1000 The grading distribution (out of 1000 total points) is pre-defined: A+ 970-1000, A 930-969, A- 900-929, B+ 870-899, B 830-869, B- 800-829, C+ 770-799, C 730-769, C- 700-729, D+ 670-699, D 630-669, D- 600-629, F 0-599 |
| Important dates: | Course Add/Drop Begins: Wednesday, August 26
Instruction Begins: Friday, August 28 First prelim: 7:30 PM, Thursday, October 8 (room[s] TBA) Fall Break Begins:, 1:10 PM, Saturday, October 10 Instruction Resumes: 7:30 AM, Wednesday October 14 Second prelim: 7:30 PM, Tuesday, November 10 (room[s] TBA) Thanksgiving Recess Begins: 1:10 PM, Wednesday, November 25 Instruction Resumes: 7:30 AM, Monday, November 30 Last Day of Class: Friday, December 4 Last Day of Classes: Saturday, December 5 Final exam: Thursday, Dec 10, 2:00 - 4:30 pm |
Outline of topics covered: (approximate & subject to change)
| Topic | Week(s) | O&L: Stat Meth | |
| Administration & Intro | 1 | 1.1-1.6, 2.1-2.5 | |
| Descriptive Statistics | 2 | 3.1-3.7 | |
| Probability | 3 & 4 | 4.1-4.10 | |
| Random Sampling, Sampling Distributions, Central Limit Theorem | 5 | 4.12-4.13 | |
| One sample inference for location parameters | 5 & 6 | 5.1-5.7 | |
| Two sample inference for location parameters | 7 | 6.1-6.6 | |
| Inference about variances | 8 | 7.1-7.3 | |
| Inference for several means (ANOVA) | 8 & 9 | 7.4, 8.1-8.4, 8.6 | |
| Contrasts and Multiple Comparisons | 9 | 9.1-9.5 | |
| Simple linear regression & Correlation | 10 & 11 | 11.1-11.5, 11.7 | |
| Multiple linear regression | 11 & 12 | 12.1-12.5 | |
| Categorical Data | 12 & 13 | 10.1-10.6, 10.8 | |
| Logistic & Poisson Regression (if time) | 13 - 15 | 12.8 |
General Homework Policies:
Academic Integrity:
Each student in this course is expected to abide by the Cornell
University Code of Academic Integrity. Students must in no way
misrepresent their work, fraudulently or unfairly advance their
academic status, or be a party to another student's failure to
maintain academic integrity. A full statement of this code may be
found at: http://cuinfo.cornell.edu/Academic/AIC.html.
Accommodations for Students with Disabilities:
In compliance with the Cornell University policy and equal access
laws, Professor Strawderman is available to discuss appropriate
academic accommodations that may be required for student with
disabilities. Except for unusual circumstances, requests for academic
accommodations must be made during the first three weeks of the
semester so that appropriate arrangements can be made. Students are
encouraged to register with Student Disability Services to verify
their eligibility for appropriate accommodations.