Statistics Lectures - 8: Probability

Related Pages
6: Skewness, Normal Distribution, Empirical Rule
7: Z-Scores
9: Permutations & Combinations
10: Discrete & Continuous Random Variable
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Statistics - Lecture 21: The Basics of Probability

Probability is a measure of the likelihood of an event.
A sample space is a collection of all possible outcomes.
An event with a probability of 0 is impossible (it will never happen).
An event with a probability of 1 is certain (it will always occur).

Statistics - Lecture 22: Addition Rule (Probability “Or”)

Two events are mutually exclusive if they cannot occur at the same time.
Addition rule for mutually exclusive events:
P(A or B) = P(A) + P(B)

Statistics - Lecture 23: Multiplication Rule (Probability “And”)

Two events are independent if they do not affect one another.
Multiplication Rule for independent events:
P(A and B) = P(A) × P(B)
General Multiplication Rule for Dependent or Conditional Event:
P(A and B) = P(A) × P(B | A)

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Statistics Lecture Series - Table Of Contents

• Descriptive Statistics
• Probability
• Correlation
• Inferential Statistics

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