Master Windows Internals - Kernel Programming, Debugging & Architecture
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Learn about the expected value (mean) of probability distributions, one of the most fundamental concepts for understanding random variables. Explore how to define and calculate expected values mathematically, understand the relationship between sample means and theoretical expected values, and discover when expected values can be misleading in practical applications. Examine the concept of moments in probability theory and compare three key measures of central tendency: mode, mean, and median. Master statistical estimation techniques for computing means from data samples and gain insights into how expected values serve as powerful tools for comparing different probability distributions.
Syllabus
00:00 Intro
01:02 Defining the Expected Value
04:17 Sample Mean & Expected Value
07:25 Misleading Expected Values
08:51 Introducing Moments
10:43 Mode, Mean, and Median
14:40 Outro
Taught by
Steve Brunton