STAT 401B: Statistical Methods for Research
Workers
Engineering, Mathematical and Physical Sciences Section
Fall 2014
SYLLABUS (and other useful information)
Instructor: Mervyn Marasinghe, Office: 2417, Snedecor, Phone: 4-7774, e-mail:
mervyn@iastate.edu,
Lecture: MWF 1 p.m., Hort 0118
Office Hours: MW 9:00-10:00, R 11-12
Please feel free to send e-mail to me anytime with questions or comments.
Lab Assistant: Chen Hua ; Office: 3418 Snedecor ; e-mail: chua@iastate.edu
Laboratory: R 2:00-4:00 p.m., Gilman 2272 (this lab is part of your class; attendance
is required)
Office Hours: MW 11-12, T 4:10-5:00 (meet in Room 2404 , Snedecor Hall)
Text: An Introduction to Statistical Methods and Data Analysis by Lyman Ott & Michael
Longnecker, 6th Edition, 2010
Course Objectives: As stated in the preface of the text book "...to prepare students to deal with
solving problems encountered in research projects, decision making based on data,, and general
life experiences beyond the classroom and university..." is the primary goal. In order to achieve
this goal, statistical methods available for analyzing experimental and observational data will be
presented. How to use parametric models to make inferences from the data will be a basic
objective. In comparison to an introductory level class, a deeper understanding of the basic
concepts will be stressed. For example, understanding the difference between a population and a
sample is a fundamental objective of this course. While it is important to know how to estimate
the slope of a regression line from data it is also important to know how to interpret it. Similarly,
even in Stat101, students learn how to calculate a confidence interval for a population parameter.
But would they be prepared to explain what the term “confidence” means to their advisor or to
their employer?
Course Outline (tentative): To view this click on OUTLINE
Evaluation:
Grading:
Lab assignments:
100 pts
approx. weekly (9 lab assignments)
Exam I:
Exam II:
Final Exam:
100 pts
100 pts
200 pts
Oct 09 (Gilman 2272; 2:10-3:40 p.m.)
Nov 13 (Gilman 2272; 2:10-3:40 p.m.)
Dec 18 (Hort 0118;12:00-2:00 p.m.)
Final Grade: Final course grades will be determined by the total points earned from the labs
and exams according to the schedule above divided by 500 and expressed as a percentage. The
final percent will be used to rank students and determine cut-off points for assigning letter
grades. First, letter grades A, B, C, D, will be assigned to those with percentages in
the ranges 90-100, 80-89, 70-79, 60-69 respectively. The cut-off points may be adjusted
(lowered) later depending on the performance of the entire class to increase the proportion of
students in the class earning each grade. Plus/minus grades will be assigned to scores near final
cut-off points.
Exams:
• Plus/Minus grading will be used.
• Makeup exams will be given only if you contact me and get approval prior to the
scheduled exam.
• All exams are closed book meaning you will not be allowed to use the textbook or notes
during the exam.
• An 8.5x11 inch formula sheet prepared by the student will be allowed.
• In the past, students have viewed the preparation of the formula sheet as a useful way to
review of the material covered.
• Any statistical tables needed will be provided.
• Cell phones or other electronic devices (e.g., PDA's, iPods, ear phones, etc.) will not
be allowed in the exam room.
• You must bring pencils, eraser and scratch paper and a calculator for all exams.
• Note that Midterm Exams will be given during regular lab hours (locations to be
announced).
• Final must be taken at the scheduled date and time.
Lectures and Assignments: Please read the assigned chapter(s) prior to the start of the lectures.
My lectures will cover the same concepts, but I will often use different examples and may use a
different presentation. It will probably help to reread the chapter(s) after the relevant
lectures and do the suggested exercises. A set of typed notes, also projected as slides in class,
is also available on the web pages as pdf files. Students may print these out if they wish. As I
will not go slide by slide during the lectures it is up to you to be aware of the material being
covered, as I will not proceed in the exact sequence of topics as presented in the text book. I will
supplement these slides with typed or had-written handouts, copies of pages from the text book,
as well as JMP output. As the examples covered in class are very important as the lab
assignments and exam problems closely follow these, it is good practice to organize these in a
way they can easily referenced during the lab and when studying for exams..
Laboratory: Scheduled lab time will be used for several different activities:
• Discussion, Q/A, and help on doing lab assignments.
• Some hands-on illustrations of computing examples.
• For an additional lecture when regular class time will be used for an Exam review.
•
For administering scheduled Mid-term Exams in another classroom to be announced.
It is urged to use the lab time well. Use it to ask questions on or for more explanation of topics
you did not understand well during the regular lecture. Your instructor and the TA are in the lab
during this period for this purpose.
Lab Assignments: Lab assignments are distributed and due at the lab session. Intent of these
assignments is to increase understanding of concepts learned introduced in lectures and to gain
practice in applying these concepts and associated computations. Discussion with friends and
classmates is fully encouraged in completing these assignments. However, copying of others
work is not a good way to learn and will not be tolerated. Late homework will not be accepted
by your TA.
Other Matters:
Computing: This class focuses on statistical concepts, not details of a specific computing
package. We will use JMP in class and many examples of its use for solving in class and lab
problems will be made available. No attempt will be made to give details of the use of the
language for general data analysis nor is it expected that students become experts in the use of
JMP. However, students may find it useful to learn JMP as much as possible while enrolled in
this class as they might find it extremely useful for performing statistical analysis of their
research work in the future. The TA will help you with learning JMP as well as specific
questions you may have. Outside of Snedecor Hall, JMP is available under MS Windows in labs
such as Carver 205 and Durham 139. For those who are interested in learning more about JMP,
the JMP documentation "Introductory Guide" and the "User's Guide", available as a
dropdown menu items in JMP software startup window on the desktop is adequate.
Academic Dishonesty: This class will follow the Iowa State University policy on academic
dishonesty found in the ISU catalog. A score of zero will be given for the entire assignment in
which the academic dishonesty occurred. In addition, anyone suspected of academic dishonesty
will be reported to the Dean of Students Office:
http://www.dso.iastate.edu/ja/academic/misconduct.html
Disability Accomodation: Iowa State University complies with the Americans with Disabilities
Act and Sect 504 of the Rehabilitation Act. If you have a documented disability and anticipate
needing accommodations in this course, please make arrangements to meet with Professor
Marasinghe within the first two weeks of the semester or as soon as you become aware of your
need.. Retroactive request for accommodations will not be honored. Please have Disability
Resources (Disability Resources Office) complete a SAAR form verifying your disability and
specifying the accommodations you will need for this course. You will need to present this form
to Professor Marasinghe at the first meeting.
Dead Week: This class follows the Iowa State University Dead Week policy as noted in section
10.6.4 of the Faculty Handbook http://www.provost.iastate.edu/resources/faculty-handbook .
Harassment and Discrimination: Iowa State University strives to maintain our campus as a
place of work and study for faculty, staff, and students that is free of all forms of prohibited
discrimination and harassment based upon race, ethnicity, sex (including sexual assault),
pregnancy, color, religion, national origin, physical or mental disability, age, marital status,
sexual orientation, gender identity, genetic information, or status as a U.S. veteran. Any student
who has concerns about such behavior should contact his/her instructor, Student Assistance at
515-294-1020 or email dso-sas@iastate.edu, or the Office of Equal Opportunity and Compliance
at 515-294-7612.
Religious Accommodation: If an academic or work requirement conflicts with your religious
practices and/or observances, you may request reasonable accommodations. Your request must
be in writing, and your instructor or supervisor will review the request. You or your instructor
may also seek assistance from the Dean of Students Office or the Office of Equal Opportunity
and Compliance.
Contact Information: If you are experiencing, or have experienced, a problem with any of the
above issues, email academicissues@iastate.edu.