STAT 302: Statistical Methods

Spring 2012

Class Website / Syllabus

http://302.ddahl.org

Instructor

Dr. David Dahl
dr.dahl@ddahl.org
436 Blocker
979-845-3141

Teaching Assistant

Jincheol Park
302ta@ddahl.org
506 Blocker

Teaching Assistant

Yuan Qu
302ta@ddahl.org
405A Blocker

Times and Places

Section	Lab	Lecture
506	M, 10:20-11:10am in 162 Blocker	W F, 11:30-12:20pm in 169 Blocker
507	M, 11:30-12:20pm in 162 Blocker	W F, 11:30-12:20pm in 169 Blocker
508	M, 12:40-1:30pm in 162 Blocker	W F, 12:40-1:30pm in 169 Blocker
509	M, 1:50-2:40pm in 162 Blocker	W F, 12:40-1:30pm in 169 Blocker

Getting Help in Person

Day	Time	Location	From Whom?
Monday	5:00-8:00pm	162 Blocker	Yuan and other TA's
Tuesday	8:30-9:30am	405A Blocker	Yuan
	3:30-4:30pm	506 Blocker	Jinchoel
	5:00-8:00pm	162 Blocker	Jinchoel and other TA's
Wednesday	8:00-9:00am	405A Blocker	Yuan
	10:00-11:20am	436 Blocker	Dr. Dahl
	3:30-4:30pm	506 Blocker	Jinchoel
	5:00-8:00pm	162 Blocker	Jinchoel and other TA's
Thursday	8:30-9:30am	405A Blocker	Yuan
	11:00-noon	506 Blocker	Jinchoel
	5:00-8:00pm	162 Blocker	Yuan and other TA's
Friday	10:00-11:20am	436 Blocker	Dr. Dahl
Sunday	3:00-6:00pm	162 Blocker	Other TA's

Getting Help Electronically

Send e-mail to 302ta@ddahl.org.
E-mails are handled by Jinchoel and Yuan, and escalated to Dr. Dahl as needed.

Resources

Blog: Announcements, corrections, and commonly-asked questions.
Materials: Review sheets, exams, etc.
Personal Information: eBook Activation Code, WebAssign Class Key, etc.
StatSwami: Online tools by Dr. Dahl.
Tables: Z, t, and χ2 tables.

Lecture Schedule

Number	Date	Topic	Reading
1	01/18	Syllabus, overview of statistics
2	01/20	Data types, graphical summaries	Chapter 1
3	01/25	Numerical summaries	Chapter 2
4	01/27	Probability	Chapters 9 and 10
5	02/01	Probability	Chapters 9 and 10
6	02/03	Random variables	Chapters 9 and 12
7	02/08	Normal distribution	Chapter 11
8	02/10	Sampling distributions	Chapter 13
9	02/15	Central Limit Theorem	Chapter 13
10	02/17	Confidence intervals for a mean	Chapter 14.1-14.3

Textbook

Our online textbook is The Practice of Statistics in the Life Sciences, by Brigitte Baldi and David Moore is the required reading for the course.
Please register online using these instructions. You will need the "eBook Activation Code" from your "Personal Information" above.

Homework

Homework will be completed online using the WebAssign system.
Please register online using these instructions. You will need the "WebAssign Class Key" from your "Personal Information" above.
Homework will typically be posted on Fridays and will be due the following Thursday nights by 11:45pm. Late homework is not accepted. Difficulties with computing are not an acceptable excuse for not finishing homework.

Labs

Lab time will involve in-class exercises conducted by Jinchoel and Yuan.
The labs are designed to reinforce concepts taught in lecture, to provide practice applying the methods, and to help with homework.
Labs are due at the end of class. Late labs are not accepted.
Labs are graded on the following scale:
- 2 points for doing the entire lab.
- 1 point for attempting only some of the lab.
- 0 points if you miss the lab.

Quizzes

Throughout the semester, frequent unannounced quizzes will be given during lecture.
You are responsible for bring your own paper and a pencil/pen in the event of an unannounced quiz.
There are no makeup quizzes.

Exams

Each exam has multiple choice and true/false questions. You will need to bring your own large grey Scantron form.
Each exam is cumulative, but emphasizes recently covered material.
You will need a basic calculator that has the square root function. More advanced calculators are permitted only if you do not use the advanced functionality.
Dates:
- Midterm 1: Monday, March 5 in 162 Blocker at your regular lab time.
- Midterm 2: Monday, April 23 in 162 Blocker at your regular lab time.
- Final (Sections 506 & 507): Monday, May 7 in 169 Blocker from 10:30am - 12:30pm.
- Final (Sections 508 & 509): Monday, May 7 in 169 Blocker from 3:30pm - 5:30pm.
You must take the exams according the schedule for your section.

Course Grade

Total scores are computed using the following weights:
- 10% -- Homework
- 10% -- Labs
- 10% -- Quizzes
- 20% -- Midterm 1
- 20% -- Midterm 2
- 30% -- Final

Course grades are assigned by total scores using the following scale:

90%	≤	score	≤	100%	⇒	A
80%	≤	score	<	90%	⇒	B
70%	≤	score	<	80%	⇒	C
60%	≤	score	<	70%	⇒	D
0%	≤	score	<	60%	⇒	F

University Excused Absences

Definition: Details of what constitutes a University Excused Absence is available in the Student Rules.
Homework: Through the course of the semester, many students will have University Excused Absences. To account for this, your lowest two homework percentages will automatically be dropped when computing your grade. If you miss more than two homeworks due to unforseen University Excused Absences, you must provide documentation for all University Excused Absences and the missed work will be dropped when computing your grade.
Lab: Likewise, your lowest two lab scores will be automatically dropped. You must provide documentation for all University Excused Absences in order to drop more than two lab scores.
Quizzes: Your lowest quiz score will be automatically dropped. You must provide documentation for all University Excused Absences in order to drop more than one quiz score.
Exams: Quoting from the University Excused Absence section of the Student Rules, "To be excused the student must notify his or her instructor in writing (acknowledged e-mail message is acceptable) prior to the date of absence if such notification is feasible. In cases where advance notification is not feasible (e.g. accident, or emergency) the student must provide notification by the end of the second working day after the absence. This notification should include an explanation of why notice could not be sent prior to the class. If needed, the student must provide additional documentation substantiating the reason for the absence, that is satisfactory to the instructor, within one week of the last date of the absence." In short, if you are unable to take an exam at the scheduled time you must notify Dr. Dahl as soon as possible. Missed exams will be a given zero points except for a University Excused Absence. In that case, Dr. Dahl (at his discretion) may either administer a makeup exam or use the final exam grade to compensate for the missed exam.
Incomplete Grade: An incomplete grade will be given only if a student, due to a University Excused Absence, is unable to make up the final before the semester grades are due.

Course Objectives and Prerequisites

Statistics is the science of learning from data. The main learning objective of the course is for students to be able to analyze and interprete data that is limited and variable to make conclusions regarding populations. Topic covered include an introduction to concepts of random sampling and statistical inference; estimation and testing hypotheses of means and variances, analysis of variance, regression analysis; chi-square tests. The course is intended for students in biological sciences or agriculture (except agricultural economics). Prerequisites are MATH 141 or 166 or equivalent.

Class Attendance

Class attendance is an important part of your success in the class. The syllabus, homework assignments, exam dates, etc. may be changed by in-class announcements. If you are absent, please check with a classmate regarding the lecture material and announcements. Outside of class, Dr. Dahl and the graduate students are best-able to help those who attend class.

Statement on Disabilities

The Americans with Disabilities Act (ADA) is a federal anti-discrimination statute that provides comprehensive civil rights protection for persons with disabilities. Among other things, this legislation requires that all students with disabilities be guaranteed a learning environment that provides for reasonable accommodation for their disabilities. If you believe you have a disability requiring an accommodation, please contact the Office of Disabilities Services in Room B118, Cain Hall. The phone number is 845-1637.

Statement on Plagiarism

The handouts used in this course are copyrighted. By "handouts," I mean all materials generated for this class, which include but are not limited to syllabi, quizzes, exams, lab problems, in-class materials, review sheets, and additional problem sets. Because these materials are copyrighted, you do not have the right to copy the handouts, unless I expressly grant permission. As commonly defined, plagiarism consists of passing off as one's own ideas, words, writing, etc., which belong to another. In accordance with this definition, you are committing plagiarism if you copy the work of another person and turn it in as your own, even if you should have the permission of that person. Plagiarism is one of the worst academic sins, for the plagiarist destroys the trust among colleagues without which research cannot be safely communicated. If you have any questions regarding plagiarism, please consult the latest issue of the Texas A&M University Student Rules, under the section "Scholastic Dishonesty."

Academic Integrity Statement:

The Aggie Honor Code states, "An Aggie does not lie, cheat, or steal or tolerate those who do." Please refer to the Honor Council Rules and Procedures on the web: http://www.tamu.edu/aggiehonor