Probability & Statistics (English)

   Thursday, December 14, 2023   

Starting a new Lecture Notes Series on Probability & Statistics

Youtube Lecture Playlist Credits 

Channel Name: Dopamine

So Let Us Start to This Journey of Learning 

Probability & Statistics By Lecture Notes together!

Lecture 1: L 1 | Probability Intro I | Digital Communication | Probability & Statistics

Lecture 2: L 2 | Conditional Probability | Probability Intro II | Probability & Statistics

Lecture 3: L 3 | Baye's Theorem | Probability & Statistics

Lecture 4: L 4 | Probability Numericals I | Solved Questions

Lecture 5: L 5 | Probability Numericals II | Solved Questions

Lecture 6: L 6 | Probability Numericals III | Solved Questions

Lecture 7: L 7 | Probability Numericals IV | Solved Questions

Lecture 8: L 8 | Probability Numericals V | Solved Questions

Lecture 9: L 9 | Probability Numericals VI Solved Questions

Lecture 10: Random Variable With Animation | Complete Analysis With Examples

Lecture 11: L 11 | PMF, CDF, PDF | Probability & Statistics

Lecture 12: L 12 | PMF, CDF, PDF | Probability & Statistics

Lecture 13: L 13 | PMF, CDF, PDF | Probability & Statistics

Lecture 14: L 14 | Mean | Variance | Standard Deviation

Lecture 15: L 15 | Mean | Variance | Standard Deviation

Lecture 16: L 16 | Mean | Variance | Standard Deviation

Lecture 17: L 17 | Degenerate | Bernoulli | Binomial | Poisson | Geometric

Lecture 18: L 18 | Uniform | Exponential | Gamma | Weibull Distribution

Lecture 19: L 19 | Gaussian Distribution | CDF of Gaussian Distribution

Lecture 20: L 20 | Mean & Variance of Gaussian Distribution

Lecture 21: L 21 | 2 D Random Variable | Probability & Statistics

Lecture 22: L 22 | 2D Random Variable Questions | Probability & Statistics

Lecture 23: L 23 | 2D Random Variable Questions | Probability & Statistics

Lecture 24: L 24 | Marginal & Conditional Distribution | Probability & Statistics

Lecture 25: 2 Dimensional Random Variable

Lecture 26: L 25 | Marginal & Conditional Distribution Questions

Lecture 27: L 26 | Mathematical Expectations | 2 D Random Variable

Lecture 28: L 27 | Cauchy Schwarz Inequality | Probability & Statistics

Lecture 29: L 28 | Error Function | Complimentary Error Function

Lecture 30: L 29 | Chebyshev Inequality | Probability & Statistics

Lecture 31: Lec 30 | Correlation | Probability & Statistics

Lecture 32: Lec 31 | Correlation Question | Probability & Statistics

Lecture 33: Lec 32 | Central Limit Theorem | Probability & Statistics

Lecture 34: L 33 | Central Limit Theorem Questions | Probability & Statistics

Lecture 35: L 34 | Random Process | Probability & Statistics

Lecture 36: L 35 | Classification of Random Process

Lecture 37: Mean and Variance Practice Questions | Numericals on Random Variable

Lecture 38: L 36 | Ergodic Process | Probability & Statistics

Lecture 39: L 37 | Random Process Practice Question | Probability & Statistics

Lecture 40: L 38 | Random Process Practice Questions 2

Lecture 41: L 39 | PSD | Power Spectral Density | Probability & Statistics

Lecture 42: L 40 | PSD Practice Questions

Lecture 43: L 41 | Gaussian process | Probability & Statistics

Lecture 44: L 42 | Multiple random process | Probability & Statistics

Lecture 45: Random Process Numerical | Stationarity

Lecture 46: Random Process Numerical | Stationarity

Lecture 47: Random Process Numerical | Stationarity

Lecture 48: Autocorrelation Function Numerical | Random Process