STU2004 Applied Probability 1
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Conditional Probability
Bayes' Theorem
Conditional Probability
Cumulative Distribution Function
Law of Total Probability
Probability Mass Function
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Distributions
Normal Distribution
Normal Distribution
Z-Score
Bernoulli Distribution
Binomial Distribution
continuity correction
Exponential Distribution
Geometric Distribution
Memoryless Distribution
Poisson Distribution
Probability Density Function
Probability Distribution
Uniform Distribution
Empirical law of large numbers
Deterministic
Empirical law of large numbers
Tosses of a coin (graph)
Hypothesis Testing
Alternative Hypothesis
Chi-Square Test
Hypothesis Test
Null Hypothesis
P-value
Significance Level
Unit Interval
Joint Probability
Joint Probability
Joint Probability Distribution
Marginal Probability
Random Numbers
Combination Operator
Congruence Generator
Linear Congruential Generator
Multiplicative congruential generator
Pseudo random numbers
Quadratic Congruential Generator
Random Number Generation
Random Numbers in 0, 1
True random numbers
Random Variables
Categorical Variable
Continuous Random Variable
Discrete Random Variable
Discrete Uniform Random Variable
Expected Value
Geometric Random Variable
Independence
Mutually Exclusive Events
Poisson Random Variable
Probability Function
Random Variable
Standard Deviation
Variance
Sampling
Average
Equally likely events
Event
Experiment
Monte Carlo Simulation
Relative Frequency
Sample Point
Sample Space
Weighted Average
Sets
Additive Law
Cardinality
Independence
Partition
Probability of complementary events
Probability of intersection events
Probability
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Normal Distribution Tables
Provided Distributions
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Dec 11, 2024
1 min read
Tijms, “Understanding Probability” (3rd edition, Cambridge 2012)
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