INTRODUCTION TO PROBABILITY AND STATISTICS
- Course
- MATH205 - INTRODUCTION TO PROBABILITY AND STATISTICS
- Department
- Engineering Management - English - Master
- Course Type
- Scientific Preparation
- Status
- Required
- Language
- English
- Credit
- 0
- ECTS
- 0
- T+P+L
- 3 + 0 + 0
- Course Coordinator(s)
- Dr. Olabimpe Genevieve BADRU
- Prerequisite
- -
- Keywords
- -
Course Description
The objective of this course is to introduce basic probability concepts and basic statistics. 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)
| Item | Type | Weight (%) |
|---|---|---|
| Midterm | Midterm | 40 |
| Quiz | Quiz | 10 |
| Final | Final | 50 |
| Total | 100 | |
Course outcomes
- 01 Apply(4) statistical methods in the engineering problem-solving approach
- 02 Compute(3) and interpret(3) descriptive statistics using numerical and graphical techniques
- 03 Identify(2) and apply(4) the basic concepts of probability
- 04 Apply(4) probability theory to set up tree diagrams
- 05 Apply(4) probability theory via Bayes’ Rule.
- 06 Describe(3) the properties of random variables, discrete and continuous distribution functions.
- 07 Identify(2) the basic concepts of joint probability distribution.
Course Syllabus
| Week | Topic |
|---|---|
| Week 1 | Introduction |
| Week 2 | Populations, Samples, and Processes |
| Week 3 | Pictorial and Tabular Methods in Descriptive Statistics, Measures of Location |
| Week 4 | Measures of Variability, Sample Space and Events |
| Week 5 | Axioms, Interpretations and Properties of Probability, Counting Techniques |
| Week 6 | Counting Techniques, Conditional Probability, Independence |
| Week 7 | Definition of Random Variables, Discrete Probability Distributions |
| Week 8 | Midterm Week |
| Week 9 | Discrete Probability Distributions, Expected Values |
| Week 10 | Special Discrete Prob. Distr.: Uniform, Binomial, Geometric and Poisson |
| Week 11 | Poisson Prob. Distr., Density Functions |
| Week 12 | Continuous Probability Distributions and Expected Values. |
| Week 13 | Uniform Distr., Normal and Standard Normal Distr., |
| Week 14 | Jointly Distributed Random Variables. Expected Values. |
| Week 15 | The Distribution of the Sample Mean and The Central Limit Theorem |
Reference Books & Course Materials
- 01 Jay L. Devore, Probability and Statistics for Engineering and Sciences, 8th ed., Brooks/Cole Cengage Learning
- 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
No learning outcomes have been defined.
Program Outcomes
- Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledgein these areas in complex engineering problems
- Ability to identify, formulate, and solve complex environmental problems; ability to select and apply proper analysis and modeling methods for this purpose.
- Ability to design and conduct experiments, gather data, analyze and interpret results for investigating environmental problems or discipline specific research questions.
- Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
- Ability to communicate effectively in English, both orally and in writing; knowledge of a minimum of one foreign language
- Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
- Consciousness to behave according to ethical principles and professional and ethical responsibility; knowledge on standards used in engineering practice.
- Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development.
- Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions.
Po-Lo Matrix
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