STAT 321 Probability and Statistics for Scientists and Engineers Fall 2004

Instructor: Allan Rossman
Class Times: MTuWTh 1:10-2:00, Studio Classroom (02-206)
Office: Faculty Office Building East 25-102
Phone: 756-2861 (6-2861 on campus)
Email: arossman@calpoly.edu
Office Hours: Mondays 3:10-4:00, Tuesdays 12:10-1:00, Wednesdays 4:10-5:00, Thursdays 9:10-10:00, and by appointment and by chance

Text: Probability and Statistics for Engineering and the Sciences (6^th ed.), by Jay Devore

Course Webpage: http://statweb.calpoly.edu/rossman/stat321/
Course Listserv: stat-0321-02-044@calpoly.edu

Overview: Probability is the mathematical study of uncertainty or randomness. Statistics, which may be defined as the science of gaining insight from data, is both an exciting intellectual discipline and a powerful scientific tool. The concept of uncertainty pervades our everyday lives, and the mathematics of probability has become a very useful tool in a wide variety of fields. Moreover, statistical thinking abounds in everyday life and statistical methods are used in most academic disciplines. This course is an introduction to the fundamental concepts and methods of probability with an emphasis on their applications to statistics and data analysis.

Prerequisites: The prerequisite for this course is knowledge of differential and integral calculus for one variable, covered by Math 132 or Math 142 at Cal Poly. Specifically, we will use techniques of differentiation and integration, improper integrals, L'Hopital's rule, and infinite series. There will be no review of this material; you should consult your calculus text or meet with me if problems arise. We will also make occasional use of set theoretic properties and operations; these will be reviewed very quickly at the appropriate time. No prior knowledge of or familiarity with probability or statistics is assumed or expected.

Goals: By the conclusion of the course, I hope that you have acquired:

• the ability to perform descriptive analyses of data
• an understanding of the fundamental concepts of the mathematical theory of probability, including conditional probability, random variables, probability distributions, and expectation
• the ability to perform a wide variety of probability calculations and derivations
• facility with approaching and solving practical problems and analyzing genuine data through probabilistic reasoning
• an understanding of some fundamental statistical concepts related to probability, such as significance, confidence, power, randomization, testing, and estimation
• the ability to use a computer to analyze data and to conduct simulations to solve probability problems
• skills of communicating the results of statistical analyses through graphical and verbal means
• a sense of the applicability of statistical and probabilistic thinking to everyday life and to a variety of academic fields

Class Policies: Class time will be split roughly evenly between lectures and activities. The activities are designed to lead you to discover concepts and to explore properties of probability and statistics. Most of the activities will ask you to work with a partner, and many will ask you to use the computer. We will discuss the activities after you complete them in an effort to ensure that you have garnered the intended lessons from them. During lectures, you are sincerely encouraged to interrupt with questions and comments at any time. Class attendance is very strongly encouraged, for you are responsible for everything presented in class.

Course Materials: The required text is Probability and Statistics for Engineering and the Sciences (6th ed.), by Jay Devore. You should also have a 3 1/2" IBM formatted disk, a scientific calculator, an email address, and a three-ring binder. You will need access to Minitab, Excel, and the internet outside of class. Additional handouts will be supplied in class; you are responsible for receiving and keeping these materials. The handouts will consist primarily of activities that have been designed to help you learn the material, along with some exposition. These handouts will also be available on the web in case you miss class. You will also be expected to read the text as a supplement and reference to what you learn in class.

Use of Computers: We will make fairly extensive use of computers in this course.  They will prove useful in at least three ways:

• for performing calculations and creating graphics necessary for analyzing data
• for conducting simulations to approximate long-run behavior of random phenomena
• for addressing "what if" questions that allow you to explore concepts of probability and statistics

We will make frequent use of the statistical analysis package Minitab and of Java applets available on the internet, and we will make occasional use of the spreadsheet package Excel. No prior knowledge of these software tools is assumed; you will receive detailed instructions regarding their use when the need arises. Minitab is freely available in the Studio classroom and in all ITS-run computer labs. You can download a free copy of Minitab from my.calpoly.edu (click on Technology and then Windows and then Minitab) or check out a CD to install Minitab on your own computer from the PolyConnect Lab in Kennedy Library.

Grading Policies: In order to give you a variety of opportunities to demonstrate your learning, your course grade will be determined by the following components, with relative weight as indicated:

• investigation assignments (15%)
• three midterm exams (55%; 15% for lowest score, 20% for other two)
• comprehensive final exam (30%)

Assignments: You may have noticed that this list does not include homework assignments, but I will assign optional problems from the text. I strongly encourage you to work on these problems in order to judge how well you are learning the material and prepare for the kinds of questions that will be on exams. A listing of these optional homework assignments will be maintained here.

Investigation assignments build on in-class activities and will be assigned occasionally. These are often fairly open-ended, requiring both writing and computer work. You may work with one other person on these investigations, submitting one report with both names. Word-processed reports of investigations are preferred to hand-written ones, and computer output should be integrated into the report. Investigations are due at the beginning of class on the indicated day, which will be announced in class. Late investigations will not be graded, and missed investigations can not be made up. You may drop the lowest of your investigation scores if we have nine or fewer; you may drop the two lowest if we have ten or more. A listing of investigation assignments will be maintained here.

The purposes of these assignments are:

• to give you the problem-solving practice necessary to learn, understand, and apply the concepts and techniques presented,
• to provide you with feedback regarding your understanding of the material,
• to further your discovery and exploration of course material, and
• to prepare you for the kinds of questions that will be on the exams.

Exams: The exams will be open-book and open-notes, so you should concentrate not on memorizing but rather on understanding concepts and developing problem-solving abilities. You will received detailed guidelines regarding the exams a week or so in advance.  The abilities to understand concepts, interpret results, explain reasoning, and communicate findings are at least as important as computational skills on these exams. Notice that your lowest score on a midterm will count for less weight than the others. You may make up an exam only with a written medical excuse.

Study Hints: I offer the following very simple but often ignored pieces of advice for your consideration:

1. Come to class.
2. Participate in class.
3. Work together.
4. Ask questions.
5. Review your notes.
6. Start assignments early.
7. Take the course seriously.
8. Have fun with the material.
9. Think!

Tentative Schedule: The following is always subject to change but should give you a sense for what topics we will cover and when:

Week	Dates	Topics	Sections from Text
1	Sept 20-23	Randomization, Probability, Simulation, Equal Likeliness	2.1, 2.2
2	Sept 27-30	Counting Methods, Conditional Probability, Independence	2.3, 2.4, 2.5
3	Oct 4-7	Review, Exam, Discrete Random Variables, Expectation	3.1, 3.2
4	Oct 11-14	Binomial Distributions , Other Discrete Distributions	3.3, 3.4, 3.5, 3.6
5	Oct 18-21	Continuous Random Variables, Expectation	4.1, 4.2
6	Oct 25-28	Review, Exam, Normal Distributions	4.3
7	Nov 1-4	Other Continuous Distributions, Bivariate Distributions	4.4, 4.5, 4.6, 5.1, 5.2
8	Nov 8-10	Descriptive Statistics	1.1, 1.2, 1.3, 1.4
9	Nov 15-18	Sampling Distributions, Review, Exam	5.3, 5.4, 5.5
10	Nov 22-23	Point Estimation	6.1, 6.2
11	Nov 29 – Dec 2	Confidence Intervals	7.1, 7.2, 7.3
	Dec 8, 1:10-4pm	Final Exam

Disclaimer: I am not always as organized as this lengthy syllabus might suggest. All of these details are subject to change as the course develops. I welcome and value your input.