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This statistics video tutorial provides a basic introduction into cumulative distribution functions and probability density functions. The probability density function or pdf is f(x) which describes the shape of the distribution. It can tell you if you have a uniform, exponential, or normal distribution. The cumulative distribution function or cdf allows you to calculate the area under the curve to the left of some point of interest in order to evaluate the accumulated probability.

Probability Formula Sheet:


Introduction to Probability:


Probability Formulas:


Probability Explained:


Probability With Geometry:


Probability of Complementary Events:


Conditional Probability:


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Independent and Dependent Events:


Probability of Mutual Exclusive Events:


Multiplication and Addition Rule:


Compound Probability:


Expected Value:


Probability Tree Diagrams:


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Bayes Theorem:


Probability - Binomial Distribution:


Probability - Geometric Distribution:


Probability - Poisson Distribution:


Continuous Probability Distributions:


Probability Density Functions:


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Probability - Uniform Distributions:


Probability - Exponential Distributions:


Probability - Normal Distributions (Calculus):


Probability - Standard Normal Distributions:


Probability - The Law of Large Numbers:


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Final Exams and Video Playlists:

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