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NS3 - 3.9 Poisson distribution

Poisson distribution and approximating binomial as Poisson

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NS3 - 3.8 Review of differences between binomial, negative binomial, and HG Distributions

Decision tree to help determine what the distribution of a RV is with Bernoulli trials

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NS3 - 3.7 Hypergeometric Random Variables

Hypergeometric Random variables

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NS3 - 3.6 Negative Binomial Random Variables

Negative Binomial Random Variables

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NS 3 - 3.5b Binomial Distribution Examples

Binomial Distribution Examples and the Multinomial Distribution

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NS3 - 3.5a2 Bernoulli Trials and Binomial Distribution

Binomial Distribution needs spliced together with 3.5 a1

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NS3 - 3.5a Bernoulli trials and binomial distribution

Bernoulli trials, binomial distribution

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NS3 -3.4 Four Step Procedure and Discrete Uniform Random Variables

Four step procedure to solve problems with random variables, Discrete Uniform distribution

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NS3 - 3.3 Expected value and Variance of Discrete Random Variables

Expected Value, Variance, Standard Deviation of RVs

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NS3 - 3.2 Properties of Discrete Random Variables

Probability Mass Function, using a PMF to determine probabilities, relationship between PMF and CDF

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NS3 - 3.1 What are Random Variables?

Random Variables, Continuous vs. Discrete RVs, RV notation

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NS2 - 2.8 - Conditional Probability

Bayes Rule, Conditional probability

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NS2 - 2.7 Calculating Basic Probabilities

Calculating probabilities for independent events; assume classical probabilities

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NS2 - 2.6 Ways to Determine Probabilities of Events and Counting Techniques

Subjective, Empirical, Classical Probabilities, Combinations and Permutations

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NS2 - 2.5 - Definitions and Background about Probability

Sample space, outcomes, events

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NS2 - 2.4 Probability and Set Definitions and Relationships

Probability and Randomness, Sets, Unions, Intersections

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