INTRODUCTION TO PROBABILITY AND STATISTICS
- Course
- MATH205 - INTRODUCTION TO PROBABILITY AND STATISTICS
- Department
- Basic Sciences and Humanities
- Course Type
- Course
- Status
- Required
- Language
- English
- Credit
- 4
- ECTS
- 6
- T+P+L
- 4 + 1 + 0
- Course Coordinator(s)
- Dr. Olabimpe Genevieve BADRU
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)
| 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
- L01 Apply(4) statistical methods in the engineering problem-solving approach
- L02 Compute(3) and interpret(3) descriptive statistics using numerical and graphical techniques
- L03 Identify(2) and apply(4) the basic concepts of probability
- L04 Apply(4) probability theory to set up tree diagrams
- L05 Apply(4) probability theory via Bayes’ Rule.
- L06 Describe(3) the properties of random variables, discrete and continuous distribution functions.
- L07 Identify(2) the basic concepts of joint probability distribution.
Program Outcomes
- P01 Should have sufficient knowledge in mathematics, science, and subjects specific to the relevant engineering discipline.
- P02 Should have the ability to use theoretical and applied knowledge in mathematics, science, and related engineering disciplines in complex engineering problems.
- P03 Should have the ability to detect, define, formulate, and solve complex engineering problems.
- P04 Should have the ability to select and apply appropriate analysis and modeling methods to solve complex engineering problems.
- P05 Should have the ability to design a complex system, process, device, or product to meet specific requirements under realistic constraints and conditions.
- P06 Should have the ability to apply modern design methods.
- P07 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.
- P08 Should have the ability to use information technologies effectively.
- P09 Should have the ability to design experiments, for the study of complex problems or discipline-specific research topics.
- P10 Should have the ability to conduct experiments, collect data, analyze and interpret results for the study of complex problems or discipline-specific research topics.
- P11 Should have the ability to work in intradisciplinary teams.
- P12 Should have the ability to work in interdisciplinary teams.
- P13 Should have the skills to work individually.
- P14 Should have the ability to communicate effectively verbally and in writing.
- P15 Should have the knowledge of at least one foreign language.
- P16 Should be able to write effective reports, understand written reports, and prepare design and production reports.
- P17 Should have the ability to make effective presentations.
- P18 Should have the ability to give and have clear and understandable instructions.
- P19 Should gain consciousness (awareness) about the necessity of lifelong learning.
- P20 Should have the ability to access information.
- P21 Should have the ability to follow developments in science and technology and constantly renew himself/herself.
- P22 Should gain the awareness of professional and ethical responsibility and should act in accordance with ethical principles.
- P23 Should gain knowledge about the standards used in engineering applications.
- P24 Should gain knowledge about project management, risk management, and change management practices in business life.
- P25 Should gain awareness about entrepreneurship, and innovation.
- P26 Should gain knowledge about development in sustainability.
- P27 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.
- P28 Awareness should be gained about the legal consequences of engineering solutions.
Po-Lo Matrix
| LO | P01 | P02 | P03 | P04 | P05 | P06 | P07 | P08 | P09 | P10 | P11 | P12 | P13 | P14 | P15 | P16 | P17 | P18 | P19 | P20 | P21 | P22 | P23 | P24 | P25 | P26 | P27 | P28 | Average |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| L01 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
| L02 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
| L03 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
| L04 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
| L05 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
| L06 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
| L07 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |