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Master Mathematical Tools for Electrical Engineering
Instructor: RVS Maths AcademyLanguage: Malayalam
📝 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
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