What is this course about?

The basic concepts of statistics that an engineer needs to know. The course covers the following topics:

1. Bayesian Statistics
2. Bayesian Estimation and Hypothesis Testing
3. Sample Statistics
4. Point Estimation
5. Confidence
6. Confidence for Normals
7. Hypothesis Testing
8. Comparing Populations
9. Goodness of fit
10. Modelling Dependence

What is this course about?

This course is an introduction to multivariable calculus for engineering students. The course covers the following topics:

1. Matrix Operations and Vector Spaces

• inverse of a matrix
• Gauss-Jordan elimination
• LU decomposition
• vector spaces
• inner product spaces
• linear transformations

Does any resource help with this course?

Textbook: Mathematics for Computer Science

What is this course about?

This course is an introduction to discrete mathematics for engineering students. The course covers the following topics:

What is this course about?

This course is an introduction to probability for engineering students. The course covers the following topics:

1. Probability and Counting
2. Axioms of Probability. Conditional Probabilities
3. Conditional Probability and Independence
4. Random Variables
5. Expectation, Variance, Joint PMFs
6. Conditional PMFs and Independent Random Variables
7. Continuous Random Variables
8. Multiple Continuous Random Variables
9. Continuous Bayes’ rule, Derived Random Variables
10. Correlation and Large Deviations
11. Chebyshev’s Inequality and The Central Limit Theorem

What is this course about?

This course is an introduction to linear algebra for engineering students. The course covers the following topics:

1. Matrices/Vectors

• gaussian elimination
• elementary row operations
• rank/nullity
• vector spaces
• row/column/null spaces
• systems of linear equations

Does any resource help with this course?

• Advanced Engineering Mathematics
• Math is Fun