1. |
|
Introduction and probability, Set Theory, Probability axioms (Chapter 1) |
Introduction of this class and basic theorem.
Practice the programming about probability. |
|
|
|
Sequential elements (Chapter 2) |
Understanding the sequential elements |
|
2. |
|
Sequential elements (Chapter 2) |
Understanding the sequential elements |
|
|
|
Sequential elements (Chapter 2) |
Understanding the sequential elements |
|
|
|
Dicrete random variables and PMFs (Chapter 3) |
Study random variables and way to make the PMFs |
|
3. |
|
Dicrete random variables and PMFs (Chapter 3) |
Study random variables and way to make the PMFs |
|
|
|
Dicrete random variables and PMFs (Chapter 3) |
Study random variables and way to make the PMFs |
|
4. |
|
Families of discrete rvs, functions of random variables (Chapter 3) |
Study Discret rvs and
Functions of random variables |
|
|
|
Families of discrete rvs, functions of random variables (Chapter 3) |
Study Discret rvs and
Functions of random variables |
|
5. |
|
Expected value, variance, conditional pmfs (Chpater 3) Test #1 |
Understanding Expected value, variance and Conditional pmfs |
|
|
|
Continuous random variables : pdfs and expected values (Chapter 4) |
Study continuous random variables and waty to make the pdfs |
|
6. |
|
Continuous random variables : pdfs and expected values (Chapter 4) |
Study continuous random variables and waty to make the pdfs |
|
|
|
Continuous random variables : pdfs and expected values (Chapter 4) |
Study continuous random variables and waty to make the pdfs |
|
7. |
|
Families of continous rvs : exponential & Gaussian (Chapter 4) |
Study families of continuous rvs |
|
|
|
Families of continous rvs : exponential & Gaussian (Chapter 4) |
Study families of continuous rvs |
|
|
|
Mixed rvs and conditioning (Chapter 5) |
Study mixed rvs and conditioning |
|
8. |
|
Mixed rvs and conditioning (Chapter 5) |
Study mixed rvs and conditioning |
|
|
|
Mixed rvs and conditioning (Chapter 5) |
Study mixed rvs and conditioning |
|
9. |
|
Joint PMFs & PDFs (Chapter 5) Test #2 |
Understanding joint PMFs&PDFs |
|
|
|
Functions of two RVs and correlation, covariance (Chapter 6) |
Understanding two RVs, correlation and covariance |
|
10. |
|
Functions of two RVs and correlation, covariance (Chapter 6) |
Understanding two RVs, correlation and covariance |
|
|
|
Conditioning, Conditional PDF/PMFs (Chapter 7) |
Study Conditioning and Conditional PDF/PMFs |
|
11. |
|
Conditioning, Conditional PDF/PMFs (Chapter 7) |
Study Conditioning and Conditional PDF/PMFs |
|
|
|
Conditioning, Conditional PDF/PMFs (Chapter 7) |
Study Conditioning and Conditional PDF/PMFs |
|
12. |
|
Independent RVs and Bivariate Gaussian PDFs (Chapter 7) Test #3 |
Study independent RVs and Bivariate Gaussian PDFs |
|
13. |
|
Random vectors and iid (Chapter 8) |
Understanding Random vectors and iid |
|
|
|
Moment generating functions (Chapter 9) |
Study characteristic of each moment generating functions |
|
14. |
|
Moment generating functions (Chapter 9) |
Study characteristic of each moment generating functions |
|
15. |
|
Central Limit theorem and its applications (Chapter 9) |
Introduction of central theorem and its apllications |
|