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. P01 Demonstrate comprehensive knowledge of key concepts across the breadth of effective application and use of MIS and innovative information technologies in organizations.
2. P02 Demonstrate autonomy and responsibility in managing MIS projects and improving organizational processes
3. P03 Demonstrate comprehensive understanding of appropriate enterprise frameworks, theories from the MIS to research and assess contemporary issues in the field and related allied fields and disciplines
4. P04 Apply MIS knowledge to facilitate the acquisition, development, deployment, and management of information systems
5. P05 Apply MIS knowledge to the exploitation of opportunities created by information technology innovations ensuring the alignment between MIS strategy and organizational strategy
6. P06 Demonstrate ethical reasoning in relation to crucial MIS issues such as privacy, information security, and ethical use of information
7. P07 Apply appropriate technologies and techniques to the collection and analysis of organizational and environmental data to facilitate evidence-based decision-making
8. P08 Analyse organizational data to accurately identify organizational problems and propose solutions using MIS
9. P09 Apply effective communication skills consistent with the professional environment
10. P10 Apply effective collaboration skills consistent with the professional environment

Po-Lo Matrix