SYLLABUS STAT 502: Analysis of Variance and Design

SYLLABUS STAT 502: Analysis of Variance and Design

Summer 2017

∙ INSTRUCTOR:

Dr. Durland Shumway

Office: 319 Thomas Bldg. (814) 865-3541

∙ PREREQUISITE: STAT 462 or 501.

∙ TEXT: Our textbook is a custom printing, Stat 502, ISBN 9781121669376

published by McGraw-Hill. It is the second half of Applied Linear Statistical Models, 5th Ed. By Kutner, Nachtsheim, Neter, and Li. 2005.

∙ SOFTWARE: The course will use the Statistical Software program SAS and when possible, Minitab. Both of these programs are available at no charge through the Penn State WebApps site: Minitab is more user-friendly and offers many useful features for illustrating ANOVA methods. However, it has limits and it so it will be essential for you to learn to work with SAS to handle the more advanced models that we will cover in this course. As a result, we will have most of the examples running in parallel for most of the course. Students may prefer to have a copy of these applications on the computer they will be using for the course. To find out more about where to get these applications go to the Department’s Statistical Software page:

Note: Some of you may prefer SPSS, and this may be used as well, having much of the same capacity that SAS does. However, we won’t be including instructions for SPSS in the lecture notes and when assignments specifically require SAS, SPSS won’t be acceptable. Also, please note that using R will create problems as we analyze linear mixed models. The output won’t be consistent with answer keys from SAS or Minitab, and will not be accepted as output for assignments.

∙ CONTENT: This is a course in applied analysis of variance (ANOVA) and analysis of covariance (ANCOVA), including randomization and blocking, single factor and multiple factor designs, categorical and quantitative factors, multiple comparisons, fixed and random effects, balanced and unbalanced designs, block designs, split-plot, repeated measures, and crossover designs. This is a lot of material and it is very important that you keep up. Most of these topics can be considered in terms of design issues and how to analyze them. We’ll look at both sides, although we will primarily look at the analysis side. For a course covering many similar topics from a design perspective, see STAT 503.

∙ LEARNING OBJECTIVES: As a result of successful participation in this course students will be able to:

Manipulate datasets in preparation for ANOVA
Recognize elements of treatment designs
Differentiate between fixed and random effects
Understand and be able to recognize blocking variables
Construct appropriate ANOVA statistical models for experimental settings
Include continuous covariates for ANCOVA
Analyze repeated measures in ANOVA
Apply concepts that are introduced in the class to advanced models

∙ PROCESS The general process used for this course is to describe methodology in Online Lesson Notes and in doing this worked examples are provided. Homework assignments will include problems that are similar to worked examples from the lessons, but will also include ‘challenges’ that require extending the concepts to new experimental situations. Homework problems may also include application (and interpretation) of the lecture material to experimental situations that arise in your area of academic interest.

Note: This course is highly cumulative and designed to have each weekly lesson build on the next. As such, “working ahead” is NOT allowed in this course. Please remember that this course needs to be one (of the probably many) priorities.

∙ PARTICIPATION / COMMUNICATION Each weekly lesson will have a Discussion Forum where students can post questions regarding subject matter content. The instructors will routinely monitor these discussions and when appropriate post responses. Students are strongly encouraged to provide responses for questions. Student responses will be monitored by faculty as well. Discussion Forums will be provided for review sessions. A separate Discussion Forum will also be provided for individual project work later in the course.

No course content questions will be answered via email. If you submit a question about course content you will be redirected to the discussion forum for your answer. Typically if you have a question aboutthe content of the lesson, others in class will also have that question. Sometimes an interesting discussion will develop among the students about it.

Courseemail is restricted to communication regardingadministrative questions, grades, etc. for the faculty. Emails sent to instructors outside of the course environment will not be answered. In order for the instructors to respond to any emails in a timely fashion, they MUST be submitted through Canvas. Following the grade submission at the end of the course, further correspondence should be conducted through my regular office email.

∙ AVAILABILITY: Students are welcome to post messages to us any time in the discussion forum for a particular lesson. I will try to respond within 24 hours on business days (Mon.- Fri.) and on weekends as possible. If something comes up wherein we will be away from the computer for an extended period, we will let you know.

∙ HOMEWORK: Homework (HW) is due by 12:00 midnight EST every Tuesday. To be clear, 12:00 midnight Tuesday occurs be between Tuesday evening and Wednesday morning. There will be a 24-hour ‘grace period’ wherein late homework assignments can be submitted to the dropbox but will be penalized by a 10% grade reduction. Any homework submitted after the 24 hour grace period will NOT be graded. You are encouraged to discuss homework problems with classmates via weekly discussion boards. We will monitor these (as well as course email) daily Monday-Friday and weekends as possible to respond to questions as they arise. Please not that posting Homework assignment questions on the due date may not be answered in time to be useful for meeting the submission deadline. For homework questions, if two answers are provided, the incorrect one will be graded. Homework solutions will be posted following completing of grading.

Submissions of Homework Assignments will consist of a single file, preferably a Word document or pdf file.

Also, one important part of an ANOVA course is the model statements. For all the designs we discuss, the book and the notes contain model statements. Since the model statements are so important, we may ask you to give them on homework assignments or tests. As mentioned above, you’ll need a way to write Greek letters, write subscripts and write simple algebraic expressions. Microsoft Word will do this by using the Insert > Equation function. With a little practice, this is not difficult to work with.

∙ TESTS: There will be two open book exams, and a proctored comprehensive final exam. Students are expected to do their own work on exams and no Discussion Forum will be available .for the exams. During the exams, clarification questions need to be emailed to the instructor, and replies will be copied to all students. For exam questions, if two answers are provided, the incorrect one will be graded. Exam solutions will be posted following completion of grading, and any questions regarding grading of exams need to be submitted by email within one week of the posting of the exam grades.

∙ INDIVIDUAL PROJECT: Each student will find an interesting ANOVA or ANCOVA data set from his or her own area of application, analyze it, and write a report on it. The projects will be completed on an individual-student basis. The project should not be a regression analysis or analyze count data. Regression methods can however be included in the context of Analysis of Covariance (ANCOVA). The project must have a full discussion of interpretations (including graphs), not just a statement of results. Note that recognition of completion of the project assignment does not represent an endorsement of the study reported.

Late Work:

The 24 hour grace period applies only to homework. In the event you have a conflict with an exam, you are required to contact the instructor 1 week before the exam date to arrange for an alternative testing timeframe. There will be no exam make ups after the fact.

∙ GRADING:

Questions concerning grading of exams or homework assignmentsneed to be addressed in Canvas email to the instructor within 1 week of their return to students. Questions concerning final course grades need to be addressed within 1 week following posting of course grades. Thereafter, all correspondence will be through the instructor’s regular email.

Weighting

Weekly Homework20%

Exams (2 Mid-terms and 1 Final – 20% each)60%

Individual Project20%

Grading Scale cutoffs are as follows: A, 92% or better; A-, 90; B+, 88%; B, 82%; B-, 80%; C+, 77%; C,70%; D,60%. A no-round-off policy will be used in determining final grades.

Academic Integrity Statement:

All Penn State policies regarding ethics and honorable behavior apply to this course. Academic integrity is the pursuit of scholarly activity free from fraud and deception and is an educational objective of this institution. All University policies regarding academic integrity apply to this course. Academic dishonesty includes, but is not limited to, cheating, plagiarizing, fabricating of information or citations, facilitating acts of academic dishonesty by others, having unauthorized possession of examinations, submitting work of another person or work previously used without informing the instructor, or tampering with the academic work of other students.

For any material or ideas obtained from other sources, such as the text or things you see on the web, in the library, etc., a source reference must be given. Direct quotes from any source must be identified as such.

Tests and projects are to be individual work.

All exam answers must be your own, and you must not provide any assistance to other students during exams. Any instances of academic dishonesty WILL be pursued under the University and Eberly College of Science regulations concerning academic integrity. For more information on academic integrity, see Penn State's statement on plagiarism and academic dishonesty.

The Eberly College of Science Code of Mutual Respect and Cooperation embodies the values that we hope our faculty, staff, and students possess and will endorse to make The Eberly College of Science a place where every individual feels respected and valued, as well as challenged and rewarded.

Accommodations For Students with Disabilities:

Penn State welcomes students with disabilities into the University's educational programs. If you have a disability-related need for reasonable academic adjustments in this course, contact the Office for Disability Services (ODS) at 814-863-1807 (V/TTY). For further information regarding ODS, please visit the Office for Disability Services Web site at

In order to receive consideration for course accommodations, you must contact ODS and provide documentation (see the documentation guidelines at If the documentation supports the need for academic adjustments, ODS will provide a letter identifying appropriate academic adjustments. Please share this letter and discuss the adjustments with your instructor as early in the course as possible. You must contact ODS and request academic adjustment letters at the beginning of each semester.

ABOUT THE INSTRUCTOR

Durland Shumway

I am an applied statistician, working as a faculty consultant and instructor in the Statistics Department. My background includes a BS in Wildlife Biology, a Masters in Ecology and my PhD is in Forest Science. In the course of doing research in the biological sciences I became more and more interested in the mathematical and statistical end of the research. I was tenured in the University System of Maryland at Frostburg State University and then came to Penn State as a consultant in the Statistical Consulting Center.

About our Instructional Designer - Glenn Johnson

Glenn is the “go to” person for .computer access to World Campus courses or your online notes. Glenn works extensively with the Statistics Department and his email address will appear in the Canvas directory.