📝 Key Learning Outcomes

The curriculum focuses on developing proficiency in three core areas:

• Probability Distributions (Modules 1 & 2): Students will master the concepts of discrete and continuous random variables, including their probability distributions (e.g., Binomial, Poisson, Uniform, Normal, Exponential) and statistical measures like Expectation, Mean, and Variance. It also covers joint and marginal distributions and the concept of independent random variables.

  • Discrete: Binomial, Poisson

  • Continuous: Uniform, Normal, Exponential

• Statistical Inference (Module 3): The course covers fundamental statistical inference techniques, including the construction of Confidence Intervals and performing Hypothesis Tests ($\mathbf{z}$ and $\mathbf{t}$ tests) for both large and small samples, and for population proportions.

• Random Processes (Module 4): A study of advanced concepts in Random Processes, including their classification, methods of description, stationarity (SSS, WSS), Autocorrelation functions, and Ergodicity (Mean-Ergodic Process, Correlation Ergodic Process).

COURSE POLICY

1. ·  Account Responsibility: Each account is intended for individual use only. Sharing login credentials with others is strictly prohibited and may result in account suspension or legal action.
2. Simultaneous Viewing: Watching videos on multiple devices at the same time is prohibited.
3.  Monitoring: We reserve the right to monitor device usage to ensure compliance with these policies. Access to the full course is permitted only on the initially registered devices.
4. Course Validity:Extensions to the course will not be granted after the expiration date outlined in your purchase details.