Practical Data Science using Python - Binomial Theory - Expected Value and Standard Error

The video tutorial covers the concept of mutually exclusive events and the addition rule for calculating probabilities. It explains how to determine the probability of specific outcomes in dice rolls and introduces the binomial formula for solving probability problems. The tutorial also discusses expected value and standard error, providing examples to illustrate these concepts.

What is the addition rule in probability?

Explain the concept of mutually exclusive events with examples.

How do you calculate the probability of drawing a two spotted side or a five spotted side from a dice roll?

What is the significance of the assumption that events must be mutually exclusive when applying the addition rule?

Describe the binomial formula and its application in probability problems.

What are the steps involved in solving problems using the binomial coefficient?

What is the role of the binomial coefficient in calculating probabilities?

How do you determine the expected value from a series of experiments?

What is standard error and how is it calculated?

Explain the relationship between observed value and expected value in the context of probability.