Department of Computer Science

College of Computer Studies

Ateneo de Naga University

 

COURSE INFORMATION

 

Course Code:          ICSM215

Course Title:            Probability Theory and Statistics

Credit:                     3 units

Term:                       Second Semester

School Year:            2004 – 2005

Schedule:                 12:00 Noon – 1:30 P.M. (MW) (Section Z22)

                                12:00 Noon – 1:30 P.M. (TTh) (Section Z21)

Instructor:                Bernardo R. Marquez, Ph.D.

E-mail:                     bernard@adnu.edu.ph

Consultation Hours: 2:00 P.M. – 3:00 P.M. (MW)

6:00 P.M. – 9:00 P.M. (Th)

2:00 P.M. – 4:30 P.M. (F)

Consultation Venue: P219

 

Rationale

 

Many natural and man-made processes are characterized by chance and uncertainty. To arrive at meaningful and useful conclusions about these processes, the extent and degree that chance and uncertainty are involved have to be seriously considered in the course of the investigation. Probability theory provides a powerful and precise language for studying processes with outcomes that are subject to chance. In particular, the results of data analysis through statistical methods are correctly interpreted when elements of probability are used in the analysis.

 

Course Description

 

This course covers the basic concepts and methods of probability theory and statistics. The course begins with the mathematical formulation of probability and a discussion of the different rules in evaluating the probability of an event. This is followed by the concepts of random variables, probability distributions, and mathematical expectation. The use of probability in statistics is shown in the discussion of random sampling, data description, and sampling distributions.

 

General Objectives

 

At the end of the semester, the students are expected to:

 

1.

Explain and illustrate the concepts of probability, random variable, probability distribution, and mathematical expectation.

2.

Use the rules of probability theory in solving statistical problems.

3.

Manifest appreciation of and interest in the various mathematical concepts, and demonstrate positive values and attitudes acquired from mathematics as a discipline.

 

Course Outline

 

Topics/Content Area

Time Frame (in hrs.)

   I. Probability

A. Sample space

B. Events

C. Counting sample points

D. Probability of an event

E. Additive rules

F. Conditional probability

G. Multiplicative rules

H. Bayes’ rule

18

  II. Random variables and probability distributions

A. Concept of a random variable

B. Discrete probability distributions

C. Continuous probability distributions

D. Empirical distributions

E. Joint probability distributions

12

III. Mathematical expectation

A. Mean of a random variable

B. Variance and covariance

C. Means and variances of linear combinations of random variables

D. Chebyshev’s theorem

  9

IV. Random sampling, data description, and some fundamental sampling distributions

A. Random sampling

B. Some important statistics

C. Data displays and graphical methods

D. Sampling distributions

  9

 

Note: (1) Four meetings are allotted to the four major examinations.

          (2) Some topics may be deleted or added depending on the available time.

 

Course Requirements

 

            Boardwork, Seatwork, Quizzes, Preliminary Examination, Mid-term Examination, Pre-final Examination,

and Final Examination

 

Grading Procedure

 

            CFRS = 40%CS + 10%PE + 20%ME + 10%PF + 20%FE    

                 CS = 60%Q + 40%BS

 

where:

CFRS

=

Total Converted Final Raw Score

 

CS

=

Class Standing

 

PE

=

Preliminary Examination Raw Score over the Perfect Score

 

ME

=

Mid-term Examination Raw Score over the Perfect Score

 

PF

=

Pre-final Examination Raw Score over the Perfect Score

 

FE

=

Final Examination Raw Score over the Perfect Score

 

Q

=

Total Raw Score in the Quizzes over the Total Perfect Score

 

BS

=

Boardwork\Seatwork Grade

 

Textbook

 

Walpole, Ronald E., Myers, Raymond H., and Myers, Sharon L. Probability and Statistics for Engineers and Scientists. 6th ed. New Jersey: Prentice-Hall, Inc., 1998.

 

References

 

Books

 

Kirkpatrick, Elwood G. Introductory Statistics and Probability for Engineering, Science, and Technology. Englewood Cliffs, New Jersey: Prentice-Hall, Inc., 1974.

Mendenall, William. Introduction to Probability and Statistics. 2nd ed. Belmont, California: Wadsworth Publishing Company, Inc., 1967.

Newmark, Joseph. Statistics and Probability in Modern Life. 4th ed. New York: Saunders College Publishing, 1988.

Snell, J. Laurie. Introduction to Probability. New York: Random House, Inc., 1988.

Stone, Charles J. A Course in Probability and Statistics. Belmont, California: Wadsworth Publishing Company, 1996.

 

Web Sites

 

davidmlane.com/hyperstat/index.html

ubmail.ubalt.edu/~harsham/statistics/REFSTAT.HTM

www.dartmouth.edu/~chance/

www.freestatistics.altervista.org/

www.nilesonline.com/stats/

 

Abridged Version

11-07-03 (First Printing)

11-05-04 (Second Printing)