Probability and Statistics

Course Title: Probability and Statistics

Course No: ENSH 304

Nature of the Course: THEORY

Semester: 5

Full Marks: 40 + 60

Pass Marks: 16 + 24

Credit Hours: 3

Course Description

This course focuses on statistical methods relevant to engineering applications. It covers descriptive statistics, probability distributions, sampling and statistical inference, correlation and regression, and statistical quality control.

Course Objectives

The objective of this course is to equip students with foundational knowledge in probability and statistics, focusing on core concepts essential for engineering applications. Students will develop essential skills in statistical data analysis, enabling them to apply various statistical techniques to address real-world engineering challenges. Additionally, the course emphasizes the interpretation and effective communication of statistical results, preparing students to make informed, data-driven decisions in their professional practice.

Course Contents

1. Descriptive Statistics and Basic Probability

6 hrs10 marks

1.1. Introduction to statistics and its importance in engineering

1.2. Measure of central tendency and measure of variation

1.3. Graphical representation of data: Histograms, box plots and scatter plots

1.4. Basic probability concepts, additive law, multiplicative law

1.5. Conditional probability and Bayes' theorem

2. Probability Distributions and Sampling Distribution

14 hrs15 marks

2.1. Random variables: Discrete and continuous

2.2. Expectation and variance of discrete and continuous random variables

2.3. Discrete probability distributions: Binomial, Poisson, negative Binomial

2.4. Continuous probability distributions: Normal, Gamma, Chi-Square

2.5. Population and sample

2.6. Sampling distribution of mean and proportion

2.7. Central limit theorem

3. Statistical Inference

14 hrs20 marks

3.1. Point estimations and properties of estimators

3.2. Confidence intervals for mean and proportions

3.3. Hypothesis testing, parametric and non-parametric tests, procedure of hypothesis

3.4. Hypothesis testing of mean (Single mean, two means, paired t-test and one-way)

3.5. Goodness of fit tests and independence of attributes (Chi-square and Kolmogorov–Smirnov test)

4. Correlation and Regression

6 hrs10 marks

4.1. Correlation analysis and test of linear correlation

4.2. Simple regression analysis, the concept of explained, unexplained, and total

4.3. Multiple regression analysis

5. Statistical Quality Control

5 hrs5 marks

5.1. Quality control and its importance in engineering

5.2. Control charts for variables (X-bar, R-chart, P-chat)

5.3. Six sigma concepts

Reference Books

1.Ronald, E.W., Raymond, H.M., Sharon, L.M. (2012). Probability & Statistics for Engineers & Scientists (9th edition). Boston USA: Prentice Hall.
2.Richard A.J. (2018). Probability and Statistics for Engineers (9th edition). Edinburgh Gate: Pearson Education Limited
3.Sheldon M.R. (2009). Introduction to Probability and Statistics for Engineers and Scientists (4th edition). London: Elsevier Inc.
4.Jay L.D. (2012). Probability and Statistics for Engineering and Sciences. Boston: Thomson Brooks/Cole
5.Brian S.E., Ibrsten H. (2010). A Handbook of Statistical Analyses Using R (2nd edition). London: CRC Press Taylor & Francis Croup
6.Andy F. (2018). Discovering Statistics Using IBM SPSS Statistics (5th edition). London: SAGE Publications.

Notes:

This syllabus follows the official BEI curriculum of Tribhuvan University. In case of any doubt or revision, the university’s published syllabus shall be considered authoritative. https://ioe.tu.edu.np/pages/electronics-engineering-curriculum-structure-2660

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