Probability Index

Probability is used to estimate the likely-hood of an event. Probabilities are always non-negative and sum to one.

Notation

Random Variable | Notation

In probability a random variable is denoted using capital latin letters usually X, Y, and Z or A, and B respectively.

Probability Distribution | Notation

A probability distribution is denoted like a function. Often a capital P is used for the function name, and the capital letter X is used for the argument to the function.

Conditional Probability | Notation

Conditional probability is denoted using a vertical bar between the two variables

Joint Distribution | Notation

A joint probability distribution is denoted like a function often using P as the function name. The capital letters X and Y are often used to represent the random variables of the distribution and are arguments to the function.

Expected Value | Notation

The expected value of a probability distribution is denoted as the function E(X).

Arithmetic Mean | Notation

The arithmetic mean of a data set is denoted by a horizontal bar over the variable x.

N Choose R Combination | Notation

The number of possible ways to choose r combinations from n total items is denoted using two parentheses with the n value above the r value. A subscript p or c is used to denote whether it is a combination or permutation.

N Choose R Permutation | Notation

The number of possible ways to choose r permutations from n total items is denoted using two parentheses with the n value above the r value. A subscript p or c is used to denote whether it is a combination or permutation.

Population Mean | Notation

Meaningful description here.

Standard Deviation | Notation

Meaningful description here.

Variance | Notation

Meaningful description here.

Formulas

Arithmetic Mean | Formula

The arithmetic mean, also called the sample mean, is the average of a sample space. To calculate the arithmetic mean sum all the data points in a sample space and then divide by the number of elements.

Combination | Formula

The combination formula describes the possible combinations of r elements out of a group of n elements where order does not matter.

Compound Interest | Formula

The compound interest formula calculates the growth of an initial value whos interest compounds over time. The frequency of when the interest is calculated and added to the initial amount can occur continuously,

Conditional Probability | Formula

The conditional probility formula shows how to calculate the probability of a event B, given that another event A has already occured.

Expected Value Continuous Distribution | Formula

The expected value, describes the most likely value of a probability distribution. It also describes where a probability distribution is centered.

Expected Value Discrete Distribution | Formula

To calculate the expected value of a discrete distribution multiply all of the events of the distribution with the probability of the element occuring.

Permutation | Formula

The permutation formula describes the possible permutations of r elements out of a group of n elements where order does matter.

Permutations of Set | Formula

The number of permutations of n distinct items is given by n factorial. A permutation is a unique ordering or arangment of the set of items.

Probability of Two Events | Formula

The probability of two events is given by the probability of the first event occurring given that the second event has occured multiplied by the probility of the second event occuring.

Sample Standard Deviation | Formula

The sample standard deviation formula is denoted by the greek lower case sigma symbol in the case of the population and the latin letter s for the sample.

Standard Deviation | Formula

The standard deviation formula is denoted by the greek lower case sigma symbol in the case of the population and the latin letter s for the sample.

Concepts

Random Variable | Concept

A random variable represents an event whose outcome is unknown.

Bayes Theorem | Concept

Bayes theorem describes a way of expressing conditional probability.

Joint Probability Distribution | Concept

A probability distribution is a function that describes the likeliness of a random variable to take on different values.

Normal Distribution | Concept

The normal distribution is a continuous probability distribution that appears naturally in applications of statistics and probability. The shape of the function forms a "bell-curve" which is symmetric around the mean and whose shape is described by the standard deviation.

Population Mean | Concept

The population mean is the average value of a population.

Probability Density Function | Concept

A probability density function models probability over a continuous range. The probability of an event occurring between thresholds is equal to the area under the curve between the thresholds.

Probability Distribution | Concept

A probability distribution is a function that describes the likeliness of a random variable to take on different values.

Standard Normal Distribution | Concept

The standard normal distribution is a probability density function with some unique and meaningful properties. The "standard" form is a special case of the generic normal distribution with a mean of 0 and a standard deviation of 1.

Examples

N Choose R Order Does Not Matter | Example

To calculate n choose r where order does not matter you can use the formula for four choose two combinations.

N Choose R Order Matters | Example

To calculate n choose r where order matters you can use the permuation formula.

Number of Permutations for N Distinct Items | Example

To calculate the possible permutations of n distinct items, you can take the factorial of n to get the numer of permutations.