Statistics - Probability mass function (PMF)

Thomas Bayes

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A probability mass function (PMF) defines a distribution function for discrete random variables whereas a probability density function (pdf) defines a distribution function for continuous random variables.





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Binomial Distribution
(Probability|Statistics) - Binomial Distribution

The binomial distribution is the discrete probability distribution of the number of successes in a sequence of n independent yes/no experiments, each of which yields success with probability p. The...
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Coin Flipping

discrete random_variable A Bernoulli_processBernoulli process is a repeated coin flipping, possibly with an unfair coin (but with consistent unfairness). If the coin is a fair coin, Y has...
Thomas Bayes
Rolling a die (many dice)

, and the random variable of interest is the sum S of the numbers on the two dice, then S is a discrete random variable whose distribution is described by the probability mass function. A discrete random...
Thomas Bayes
Statistics - (Probability) Density Function (PDF)

A probability density function (pdf) defines a distribution for continuous random variables whereas a Probability mass function (PMF) defines distribution for discrete random variables. The simplest...
Data System Architecture
Statistics - Discrete Variable

A discrete variable can only have values at specific values. See: Discrete_time_and_continuous_time Continuous vs Discretecontinuous numerical variables can be discrete. For instance, an integer...
Thomas Bayes
Statistics - Head

Head: the range of values where the pmf or pdf is relatively high.
Statistics Mode
Statistics - Mode (Majority, Peak) (flatness, pointiness or modality)

The mode is a measure of center. It's the score that occurs most often. Mode can be used for nominal variables (that's not true for Mean and Median). Graphically, the peak of a histogram is the mode....
Thomas Bayes
Statistics - Random Variable (Random quantity|Aleatory variable|Stochastic variable)

Random variable is also known as: random quantity, aleatory variable, or stochastic variable A random variable represents the result of a random process. The random variable value is the summary...
Skewed Distribution
Statistics - Skew (-ed Distribution|Variable)

The skew is where isfew. A positive skew means that you have few data at the right of the distribution. A negative skew means that you have few data at the left of the distribution. When distributions...
Thomas Bayes
Statistics - Tail

The tail of a distribution is the complement of the head within the support; the large set of values where the pmf or pdf is relatively low.



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