INTRODUCTION TO PROBABILITY AND STATISTICS

Course Description

The objective of this course is to introduce basic probability and statistics concepts. The focus of this course is on both applications and theory. Topics include: introduction to random variables, simple data analysis and descriptive statistics, frequency distribution, cumulative distribution, sample space, events, counting sample points (basic combinatorics), probability of an event, probability axioms, laws of probability, conditional probability, Bayes’ rule, discrete and continuous random variables, probability distributions, cumulative probability distributions, discrete and continuous probability distributions, discrete uniform, Binomial, Geometric, Hypergeometric, Poisson, Continuous uniform, Normal Disributions, Gamma and Exponential distribution, jointly distributed random variables, expectation and covariance of discrete and continuous random variables, random sampling, sampling distributions, distribution of Sample Mean, Central Limit Theorem(CLT).

INTRODUCTION TO PROBABILITY AND STATISTICS

Evaluation Tools (Active Term)

Course outcomes

1. 01 Apply(4) statistical methods in the engineering problem-solving approach
2. 02 Compute(3) and interpret(3) descriptive statistics using numerical and graphical techniques
3. 03 Identify(2) and apply(4) the basic concepts of probability
4. 04 Apply(4) probability theory to set up tree diagrams
5. 05 Apply(4) probability theory via Bayes’ Rule.
6. 06 Describe(3) the properties of random variables, discrete and continuous distribution functions.
7. 07 Identify(2) the basic concepts of joint probability distribution.

Course Syllabus

Reference Books & Course Materials

1. 01 Jay L. Devore, Probability and Statistics for Engineering and Sciences, 8th ed., Brooks/Cole Cengage Learning
2. 02 R.E.Walpole, R.H.Myers, S.L.Myers, K.Ye, Probability and Statistics for Engineers and Scientists, 7th ed., Prentice Hall, 2002.

Learning Outcomes

1. L01 Apply(4) statistical methods in the engineering problem-solving approach
2. L02 Compute(3) and interpret(3) descriptive statistics using numerical and graphical techniques
3. L03 Identify(2) and apply(4) the basic concepts of probability
4. L04 Apply(4) probability theory to set up tree diagrams
5. L05 Apply(4) probability theory via Bayes’ Rule.
6. L06 Describe(3) the properties of random variables, discrete and continuous distribution functions.
7. L07 Identify(2) the basic concepts of joint probability distribution.

Program Outcomes

1. Should be able to write effective reports, understand written reports, and prepare design and production reports.
2. Should have the ability to make effective presentations.
3. Should have the ability to give and have clear and understandable instructions.
4. Should gain consciousness (awareness) about the necessity of lifelong learning.
5. Should have the ability to access information.
6. Should have the ability to follow developments in science and technology and constantly renew himself/herself.
7. Should gain the awareness of professional and ethical responsibility and should act in accordance with ethical principles.
8. Should gain knowledge about the standards used in engineering applications.
9. Should gain knowledge about project management, risk management, and change management practices in business life.
10. Should gain awareness about entrepreneurship, and innovation.
11. Should gain knowledge about development in sustainability.
12. Should gain knowledge about the effects of engineering practices on health, environment, and security at universal and social dimensions and the problems of the age reflected in the field of engineering.
13. Awareness should be gained about the legal consequences of engineering solutions.
14. Should have sufficient knowledge in mathematics, science, and subjects specific to the relevant engineering discipline.
15. Should have the ability to use theoretical and applied knowledge in mathematics, science, and related engineering disciplines in complex engineering problems.
16. Should have the ability to detect, define, formulate, and solve complex engineering problems.
17. Should have the ability to select and apply appropriate analysis and modeling methods to solve complex engineering problems.
18. Should have the ability to design a complex system, process, device, or product to meet specific requirements under realistic constraints and conditions.
19. Should have the ability to apply modern design methods.
20. Should have the ability to develop, select, and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications.
21. Should have the ability to use information technologies effectively.
22. Should have the ability to design experiments, for the study of complex problems or discipline-specific research topics.
23. Should have the ability to conduct experiments, collect data, analyze and interpret results for the study of complex problems or discipline-specific research topics.
24. Should have the ability to work in intradisciplinary teams.
25. Should have the ability to work in interdisciplinary teams.
26. Should have the skills to work individually.
27. Should have the ability to communicate effectively verbally and in writing.
28. Should have the knowledge of at least one foreign language.

Po-Lo Matrix