Dictionary


Browse the glossary using this index

Special | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z | ALL

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A

axioms of probability

See Kolmogorov axioms

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C

Central tendency

A typical value for a distribution.

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coin toss

If it is a fair coin, then a coin toss can be regarded as random experiment.

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complement

The complement of set A contains everything that is not in the set A

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conditional probability

The measure of the probability of an event occurring, given that another event occurred.

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continuous variable

Can take an uncountable set of values.

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D

dependent variable

The value of a dependent variable depends on the value(s) of independent variable(s).

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descriptive statistics

Summaries of a given data set, which can be either of an entire population or a sample of a population.

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deterministic event

An event in which we can predict what will happen according to some model or set of equations. Once we know the starting conditions, we know the endpoint

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discrete variable

The number of values is either finite or countably infinite.

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disjoint sets

Also: disjoint sets. Two sets are disjoint when they have no element in common.

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Dispersion

Also: Variability. The extent to which a distribution is spread.

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E

expectation value

Also: expected value. Of a discrete random variable: the probability-weighted average of all possible values. Of a continuous random variable: the integral of the random variable with respect to ist probability measure.

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I

identically distributed random variable

Also: uniformly distributed variable. All outcomes of a random experiment are equally likel.

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independent variable

A change in the independent variable causes a change in the dependent variable.

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inferential statistics

Uses a random sample taken from a population to make inferences about the population.

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P

pairwise disjoint

Any two sets are two disjoint

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power set (of S)

contains all the subsets of S

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probability

A numerical description of how likely an event is to occur. The value range is between 0 and 1.

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probability distribution

A statistical function that describes all the possible values that a random variable can take.

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R

random experiment

When we cannot predict what will happen in a specific event, then this event can be regarded as random experiment. We may know the underlying process but not the outcome.

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random variable

A variable whose values depend on the outcome of a random experiment.

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S

sample space

Denoted as Omega. The set of all possible outcomes of a random experiment.

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set

A well-determined collections of objects.

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T

theory of probability

Treats the concept of probability through a set of axioms (e.g., Kolmogorov axioms).

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U

union

The union of a collection of sets is the set of all elements in the collection

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Entry link: union


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