STAT 506: Introduction to Experimental Design, Spring 2017
Office Hours: Tuesday/Thursday 10am to 11am, and by appointment. I am also available by Skype.
Preface xvii Preface This text covers the basic topics in experimental design and analysis and is intended for graduate students and advanced undergraduates. Students should have had an introductory statistical methods course at about the level of Moore and McCabe’s Introduction to the Practice of Statistics (Moore and McCabe 1999) and be familiar with t-tests, p-values, confidence intervals. Amazon.com: Student Solutions Manual Design and Analysis of Experiments, 8e Student Solutions Manual (198): Montgomery, Douglas C., Custer, Lisa, McCarville. Solutions Manual for Design and Analysis of Experiments, 8th Edition. The eighth edition of this best selling text continues to help senior and graduate students in engineering, business, and statistics-as well as working practitioners-to design and analyze experiments for improving the quality, efficiency and performance of working systems.
Office: 219C LeConte College, (803) 777-3859.
Class Meeting: Tuesday/Thursday 8:30am-9:45am in WMBB Nursing room 409 or online.
Oehlert Solution Manual
Textbook: A First Course in Design and Analysis of Experiments, by Gary W. Oehlert.
Video link for STAT 506.
Prerequisites: MATH 122 or MATH 142 or STAT 201. I am assuming some familiarity with probability and statistics at the STAT 201 level, e.g. exposure to the normal distribution, simple hypothesis testing, p-values, etc. If you have not had any probability or statistics you can learn the basics by reading through lectures 5-13 on my STAT 205 webpage.
Course description
We will cover a good portion of A First Course in Design and Analysis of Experiments, by Gary W. Oehlert. Timetable: One week: Chapters 1 and 2: introduction, randomization, paired and two-sample tests, introduction to R.
Three weeks: Chapters 3, 4, 5, and 6: completely randomized designs, one-way ANOVA, contrasts, multiple comparisons, checking assumptions.
Three weeks: Chapters 7, 8, 9, and 10: power and sample size, factorial treatment structure.
Two weeks: Chapters 11 and 12: random effects, mixed effects, nesting.
Three weeks: Chapters 13, 14, and 15: complete blocks, incomplete blocks, and confounding.
One week: Chapters 16 and 17: split plot designs, repeated measures, ANCOVA.
One week: Chapter 18: fractional factorial designs.
Learning outcomes
Learning Outcomes: by the end of the course students should be able to:
► Understand the benefits and limitations of common experimental designs;► Plan a sound experimental design, including the use of orthogonality, randomization, blocking, and replication (through a sample size analysis);
► Plan a practical experimental design, including the use of parsimonious methods when experimental resources are limited;
► Analyze factorial experiments using exploratory data analysis, informal and formal inferential methods; and
► Communicate experimental designs to technical and non-technical audiences.
Expectations
All students are expected to:Oehlert Solutions Manual
► Attend or view all class sessions. Live class attendance, for those who can do so, is highly appreciated - this includes distance students calling in with live questions during the lecture. I understand that this is not possible for some of you. You are encouraged to use a computer during class to 'play along' as we go.
► Review lecture required reading and/or notes before class. Handouts (if any) and course notes will be posted on the course webpage the day before each class.
► Attempt all of the assigned homework problems and email them to the TA by noon on the due date. Start homework SOON after it is assigned; this is especially true in a class involving computing. Do not email me about the assignment the night before it is due.
Textbook and reading
(1) Oehlert, G. (2010). A First Course in Design and Analysis of Experiments, freely available as PDF. Thanks Prof. Oehlert! (2) Course notes. These notes are adapted from Dr. Oehlert's course notes, my own notes from STAT 704-705 and STAT 205, and notes from Drs. Edwards, Grego, and Lynch in the Statistics Department.Lectures
You may (a) attend the live class in person, or (b) watch it live via web-streaming from any remote site, with call-in or instant-message capability for real-time questions, and/or (c) watch the recorded class later with rewind, pause, and fast-forward tools. Recordings will be posted within 24 hours of the class as files which can be viewed anytime. The ID is statistics (lowercase) and the password is ARTS#2016 (uppercase, no space). You can watch live at home during class time through web conferencing via Adobe Connect.Oehlert Solution Manual
Computing
The textbook uses a program called MacAnova, which although free is not commonly used. We will use the free R computing software. I will try to give enough examples for you to complete your homework assignments as we go; please let me know if you would like to see additional examples on any subject.Accommodations for disabilities
If you require special accommodations for a disability, these must be arranged in advance through the Office of Student Disability Services in room 112A LeConte (777-6142, TDD 777-6744, sasds@mailbox.sc.edu).Homework
Homework will be posted on the class website at least one week in advance of the due date; there will be about 5 to 10 homeworks. Send your homework solutions by e-mail as a single file in MS Word or PDF format to the Teaching Assistant Xichen Mou (xmou@email.sc.edu) with 'STAT 506 Homework' in the subject line (do not cc this email to me) by noon on the due date. Use only one side of each page, put your name on every page, and use page numbers. Any handwriting on papers must be clearly legible on the received paper after scanning - do not use soft pencil.Grading
The minimum percent needed for each grade is: A 90% B+ 87% B 80% C+ 77% C 70% D 60%. Those with a final course percentage under 60% receive an F.Honor Code
The official honor code is the Carolinian Creed in the Carolina Community: Student Handbook & Policy Guide. If you violate the honor code, I am required to report the case to the University's academic integrity office. If you are 'found responsible' in the ensuing deliberations, the penalty will be at least a letter grade in the course. Examples of honor code violations include but are not limited to: copying, or allowing someone else to copy, solutions to assignments; posing as another student to do assignments or exams; hiring or persuading someone else to do assignments in your place, etc. The whole point of this is to learn! Do not treat the course as an 'obstacle' to overcome; treat it as an opportunity to learn a broad variety of experimental designs and accompanying analysis methods, as well as deepening your understanding of statistics.Some additional comments
► Working together on homework problems is permitted and encouraged, but each student should write up his/her solutions independently of others (this will help you develop understanding). I will make available a voluntary email list of course participants so that you may contact each other regarding homework, etc. This is strictly voluntary; I will announce this during the first lecture.► The distance aspect of this course affords you the flexibility to attend class at your own convenience. However, I have found that students who are not disciplined will fall behind in attendance. Stay current with the lectures! Attending live (in class) or streaming is preferred. If you watch lecture later, it helps to have a set schedule, e.g. watch at the same times each week. Re-watching portions of a lecture can help with difficult concepts. If you have questions, attend office hours, make an appointment to meet me, or email me. I can also make a Skype appointment if you live far away from campus.