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00:00 - Understanding Population and sample
04:55 - case 1: when mean and variance of population is known then Sampling Distributions of Sample Mean10:00 - Coin Toss example to understand Random Variable and Sampling Distributions of Sample Mean
13:57 - Expectation of Sample mean in terms of population parameters
17:03 - Random Variable of Sample mean is unbiased estimator for population mean
24:08 - Variance of Sample mean in terms of population parameters
29:36 - Central Limit Theorem
33:00 - Learnings about Sample and population from Central Limit Theorem
36:43 - Why Central Limit Theorem is important in Machine Learning
38:24 - Standard Normal Variate, Standardisation and Z-score
47:19 - Significance of Z-score with Normal Distribution
51:20 - Using Look up table to calculate Probability involving z-score
54:09 - Some Useful links