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Important Formulas of Probability

Formulas : 21 Size : 332 kb

Contents of the Distribution PDF

List of 33 Distribution Formulas

Binomial Probability Distribution

Continuous Uniform Distribution

Discrete Uniform Distribution

Exponential Distribution

Geometric Distribution

Hypergeometric Distribution

Mean of Binomial Distribution

Mean of Geometric Distribution

Mean of Geometric Distribution given Probability of Failure

Mean of Hypergeometric Distribution

Mean of Negative Binomial Distribution

Normal Probability Distribution

Poisson Probability Distribution

Standard Deviation in Sampling Distribution of Proportion

Standard Deviation in Sampling Distribution of Proportion given Probabilities of Success and Failure

Standard Deviation of Binomial Distribution

Standard Deviation of Geometric Distribution

Standard Deviation of Hypergeometric Distribution

Standard Deviation of Negative Binomial Distribution

Standard Deviation of Poisson Distribution

Standard Deviation of Population in Sampling Distribution of Proportion

Variance in Bernoulli Distribution

Variance in Binomial Distribution

Variance in Exponential Distribution

Variance in Geometric Distribution

Variance in Sampling Distribution of Proportion

Variance in Sampling Distribution of Proportion given Probabilities of Success and Failure

Variance in Uniform Distribution

Variance of Binomial Distribution

Variance of Geometric Distribution

Variance of Hypergeometric Distribution

Variance of Negative Binomial Distribution

Z Score in Normal Distribution

Variables used in Distribution PDF

a Initial Boundary Point of Uniform Distribution
A Individual Value in Normal Distribution
b Final Boundary Point of Uniform Distribution
m_Sample Number of Items in Sample
n Sample Size
N Population Size
n_Bernoulli Number of Independent Bernoulli Trials
n_Population Number of Successes in Population
N_Population Number of Items in Population
N_Success Number of Success
n_{Total Trials} Total Number of Trials
N_Trials Number of Trials
p Probability of Success
P_{((A∪B∪C)')} Probability of Non Occurrence of Any Event
P_(A∪B∪C) Probability of Occurrence of Atleast One Event
P_{(Atleast Two)} Probability of Occurrence of Atleast Two Events
P_{(Exactly One)} Probability of Occurrence of Exactly One Event
p_BD Probability of Success in Binomial Distribution
P_Binomial Binomial Probability
P_Geometric Geometric Probability Distribution Function
P_{Hypergeometric} Hypergeometric Probability Distribution Function
P_Normal Normal Probability Distribution Function
P_Poisson Poisson's Probability Distribution Function
q Probability of Failure
q_BD Probability of Failure in Binomial Distribution
r Number of Successful Trials
x Number of Successes
x_Sample Number of Successes in Sample
Z Z Score in Normal Distribution
λ Population Parameter of Exponential Distribution
λ_Poisson Rate of Distribution
μ Mean in Normal Distribution
μ_Normal Mean of Normal Distribution
σ Standard Deviation in Normal Distribution
σ_Normal Standard Deviation of Normal Distribution
σ² Variance of Data
Σx Sum of Individual Values
Σx² Sum of Squares of Individual Values

Constants, Functions and Measurements used in Distribution PDF

Constant: pi, 3.14159265358979323846264338327950288
Archimedes' constant
Constant: e, 2.71828182845904523536028747135266249
Napier's constant
Function: C, C(n,k)
In combinatorics, the binomial coefficient is a way to represent the number of ways to choose a subset of objects from a larger set. It is also known as the "n choose k" tool.
Function: sqrt, sqrt(Number)
A square root function is a function that takes a non-negative number as an input and returns the square root of the given input number.

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