Data Science and Machine Learning (Theory and Projects) A to Z - Expectations: Definition

The video tutorial introduces the concept of expectation in statistics, explaining it as the mean or average associated with a random variable. It covers how to calculate expectation for both discrete and continuous random variables, using summation and integration respectively. An example with a Bernoulli random variable is provided to illustrate the concept. The tutorial concludes with a preview of a Python experiment to compute expectation.

What is the significance of the probability mass function (PMF) in calculating expected value?

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What would be the expected value of a biased coin toss with a probability of 0.7 for heads?

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Describe the process of computing expectation using Python as mentioned in the text.

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