CIS321

 

General Information:

 

Course: Introduction to Probability and Statistics (CIS321)

Instructor: Jorge Luis Romeu, Research Professor. Dpt. Mech. & Aerosp. Eng.

Email: jlromeu@syr.edu;Web Pages: http://myprofile.cos.com/romeu and http://web.syr.edu/~jlromeu

Required Textbooks: Miller & Freundís: Probability and Statistics for Engineers, (Richard A. Johnson).

Classes: will be held on Tuesdays/Thursdays: 3:30 to 4:50 PM in Room SOM 001; Lab on Fridays.

Class Dates: 1/17 to 5/02; Instructor reserves the right to reschedule a class, if necessary.

Office Hours: Tuesdays/Thursdays, right after class.

 

Course Objectives:

 

To introduce engineering students to the theory and practice of statistics and develop statistical thinking.

 

Requirements:

 

Students are required to have an account in the Sunix computer system for email communication with the Instructor, and among them. Students may use statistical software in the system to solve problems and small group projects. Students will be organized in teams of four to six, to collectively resolve (and also occasionally present in class) short statistics group projects.

 

Course Syllabus (Optimal):

 

1.        Introduction (Ch. 1): case study and examples of uses of statistics in problem solving.

2.        Treatment of Data (Descriptive Stats; Ch. 2): Frequency distributions, Pareto, Dot, Stem-and-leaf and other diagrams and graphs; descriptive measures and their calculations. Case study.

3.        Probability (Ch. 3): sample spaces, events, counting rules, axioms of probabilities, elementary theorems, conditional probability, Bayes theorem, mathematical expectation. Case study.

4.        Probability Distributions (Ch. 4): random variables, discrete distributions: Uniform, Binomial, Hypergeometric, Geometric, Multinomial, Poisson. Approximations. Chebyscheví theorem.

5.        Probability Densities (Ch. 5): continuous random variables and distributions: Normal and its approximation to the Binomial, Uniform, Exponential, Log-Normal, Gamma, Weibull. Joint distributions. Checking for Normality. Variable Transformations. Simulation.

6.        Sampling Distributions (Ch. 6): populations and samples, sampling distributions of the mean and the variance; Student t, F and Chi Square distributions.

7.        Inferences Concerning the Mean (Ch. 7): point and interval estimation.

9.        Applications in Reliability and QC (Ch. 15 & 17): basic concepts and formulas.

 

Grade Determination:

 

††††††††††††††† There will be one in-class exam every month: in February (descriptive and probability, Chs. 1, 2, 3), in March (discrete and continuous distributions, Chs. 4, 5), and in April (applications, Chs. 6, 7, 10, 15) and a comprehensive final. All exams will be based on, or similar to , exercises and problems seen in class, in Lab, in the readings and in the homework. A formula Sheet will be allowed. Final grades will be based upon (i) the two best monthly exams (25% each), (ii) the final (40%) and (iii) the quizes/group work (10%).

 


 

CIS321Teams, Readings andProjects

 

Engineers use statistics to solve problems and to take decisions under uncertainty. In addition, engineers often work in pluridisciplinary teams and must be able to present their work to peers and non-technical personnel. Toward these goals study groups (teams) of four to six students will be formed the first day of class. Students are free to exchange groups with another, as long as the teams remain of the same size.

 

Students will be assigned readings (see Web tutorials) and problems that they will resolve and deliver by groups. Teams will work collectively, communicating via email, meeting periodically, etc. Consultation among teams is fine, but each team will work individually. Sporadically, teams will be randomly selected to present their mini-projects in class. Homework problems will not be collected or graded, but they will serve as basis for Exam problems and questions, as well as for sporadic, unadvertised, short quizes.

 

The following Web tutorials, complementing the textbook material, will be covered in the course:

 

Data Quality and Pedigree. Romeu, J. L. AMPTIAC Newsletter. http://ammtiac.alionscience.com/pdf/1999MaterialEase9.pdf

 

Reliability Statistics I: Random Variables and Distributions. Romeu, J. L.

Journal of the Reliability Analysis Center. Vol. 9, Number 1; Page 9.

http://src.alionscience.com/pdf/1ST_Q2001.pdf

 

Statistical Assumptions of Exponential Distributions. Romeu, J. L. RAC START. Volume 8, Number 2. http://src.alionscience.com/pdf/E_ASSUME.pdf

 

Empirical Assessment of Normal and Lognormal Distribution Assumptions. Romeu, J. L. RAC START. Volume 9, Number 6. http://src.alionscience.com/pdf/NLDIST.pdf

 

Empirical Assessment of the Weibull Distribution. Romeu, J. L. RAC START. Volume 10, Number3.http://src.alionscience.com/pdf/WEIBULL.pdf

 

Graphical Comparison of Two Populations. Romeu, J. L. RAC START. Volume 9, Number 5.http://src.alionscience.com/pdf/2POP.pdf

 

Statistical Confidence. Romeu, J. L. RAC START. Volume 9, Number 4.

http://src.alionscience.com/pdf/STAT_CO.pdf

 

Reliability Estimations for the Exponential Life. Romeu, J. L. RAC START. Volume 10, Number 7. http://src.alionscience.com/pdf/R_EXP.pdf

 

Quality Control Charts. Romeu, J. L. RAC START. Volume 11, Number 4.

http://src.alionscience.com/pdf/QCCHARTS.pdf

 

Updated: I/06