Stat 5300 -- Statistical Process Control
Spring, 1999
MWF 12:30 - 1:20
Geology 302

Instructor: Michael Minnotte
Office: Lund 201-C
Phone: 797-2844
E-mail: minnotte@math.usu.edu
 Office Hours: TH 10:00 - 11:30 or by appointment

Text: Modern Industrial Statistics: Design and Control of Quality and Reliability, by Ron S. Kenett and Shelemyahu Zacks (Duxbury, 1998).
Available at the USU bookstore.

This course will focus on Part Two of the book (Chapters 9-14), although I may skip around a bit, including returning to earlier chapters to review or cover material which we may need.

Prerequisites: You must have some previous experience with general statistics. Stat 2000 or 3000 are good background, but Stat 2300, the old Stat 301 or 230, or an equivalent class at another university are all acceptable substitutes. If you are concerned about your preparation, please come see me.

Homework: I will assign homework every 1-2 weeks, usually from the text book. Please make things easy on me and yourself; make your homeworks easy to read and grade. Use one side of the paper, write neatly, and leave plenty of space. I will not grade a paper which I can't read. Also, show your work. Full credit will not, in general, be given for just the answer. If your answer is wrong, you will probably receive partial credit if you show your work, but not otherwise.

Many of the problems will involve computer work (see below). For the computational portions of such problems, you need only turn in the relevant output, together with any associated discussion and answers to specific questions. You do not need to turn in programming code.

All homework will be due in class on the due date. The grade for the homework will be reduced by 10% if it is turned in late on the due date, and another 10% for every working day it is late after that (to a minimum of 30% of the original grade) unless prior permission is given.

Finally, you may help each other with your homeworks, but I expect what you turn in to be your own work. Helping does not mean simply copying what someone else has put down.

Computer Use: We will use the SAS computer package, available on the University's VMS cluster and on the PC's in the Ag. Science, Merrill Library, and TSC computer labs.

Tests: There will be a midterm in class the week of February 15, and the final will be Tuesday, May 4, from 11:30 to 1:20. Both tests will be open book and open notes, and will be similar to the types of problems in the homework.

Grades: For each person I will compute an overall score according to the formula

40% Homework + 20% Midterm + 40% Final Exam
and will assign grades accordingly. There is no fixed grade profile for this class: if everyone does well, everyone can get an A.

Posting Grades: We are no longer allowed to post grades by social security number. If you wish your grade posted by my door at the end of the quarter, you must provide me with a signed written statement giving me permission to do so, and giving me a code name I can use to identify your grade. The statement should say something like ``I give Dr. Minnotte permission to post my grade for Stat 5300 under the code name XXXX.'' All grades for which I have such authorization will be posted as soon as possible after the final.

Disability Policy: If a student has a disability that will likely require some accomodation by the instructor, the student must contact the instructor and document the disability through the Disability Resource Center, preferably during the first week of the course. Any requests for special considerations relating to attendance, pedagogy, taking of examinations, etc. must be discussed with and approved by the instructor. In cooperation with the Disability Resource Center, course materials can be provided in alternative formats - large print, audio, diskette or Braille.

The above schedule and procedures in this course are subject to change in the event of extenuating circumstances.

Gauge data (homework 9). From Levine, Ramsey, Berenson, Business Statistics for Quality and Productivity
Invoice data (homework 9). (LRB)
Water lead concentrations data (homework 10). (LRB)
Vehicle flushness data (homework 10). (LRB)
Book club data (homework 11). (LRB)
Senator call records data (homework 11). (LRB)
Catfood weights data (homework 12). (LRB)
Blood sugar data (homework 12). From Mitra, Fundamentals of Quality Control and Improvement


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Last updated: April 26, 1999