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  2. Dependent and independent variables - Wikipedia

    en.wikipedia.org/wiki/Dependent_and_independent...

    In mathematics, a function is a rule for taking an input (in the simplest case, a number or set of numbers) [5] and providing an output (which may also be a number). [5] A symbol that stands for an arbitrary input is called an independent variable, while a symbol that stands for an arbitrary output is called a dependent variable. [6]

  3. Independence (probability theory) - Wikipedia

    en.wikipedia.org/wiki/Independence_(probability...

    Independence is a fundamental notion in probability theory, as in statistics and the theory of stochastic processes.Two events are independent, statistically independent, or stochastically independent [1] if, informally speaking, the occurrence of one does not affect the probability of occurrence of the other or, equivalently, does not affect the odds.

  4. Conditional independence - Wikipedia

    en.wikipedia.org/wiki/Conditional_independence

    Conditional independence is usually formulated in terms of conditional probability, as a special case where the probability of the hypothesis given the uninformative observation is equal to the probability without. If is the hypothesis, and and are observations, conditional independence can be stated as an equality:

  5. Variable (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Variable_(mathematics)

    In mathematics, a variable (from Latin variabilis, "changeable") is a symbol, typically a letter, that holds a place for constants, often numbers. [1][2][3][4][5][6] One say colloquially that the variable represents or denotes the object, and that the object is the value of the variable. Originally, the term "variable" was used primarily for ...

  6. Independent and identically distributed random variables

    en.wikipedia.org/wiki/Independent_and...

    In probability theory and statistics, a collection of random variables is independent and identically distributed (i.i.d., iid, or IID) if each random variable has the same probability distribution as the others and all are mutually independent. [1] IID was first defined in statistics and finds application in many fields, such as data mining ...

  7. Prior probability - Wikipedia

    en.wikipedia.org/wiki/Prior_probability

    An informative prior expresses specific, definite information about a variable. An example is a prior distribution for the temperature at noon tomorrow. A reasonable approach is to make the prior a normal distribution with expected value equal to today's noontime temperature, with variance equal to the day-to-day variance of atmospheric temperature, or a distribution of the temperature for ...

  8. Student's t-test - Wikipedia

    en.wikipedia.org/wiki/Student's_t-test

    Student's t-test is a statistical test used to test whether the difference between the response of two groups is statistically significant or not. It is any statistical hypothesis test in which the test statistic follows a Student's t -distribution under the null hypothesis. It is most commonly applied when the test statistic would follow a ...

  9. Conditional dependence - Wikipedia

    en.wikipedia.org/wiki/Conditional_Dependence

    Conditional dependence. In probability theory, conditional dependence is a relationship between two or more events that are dependent when a third event occurs. [1][2] For example, if and are two events that individually increase the probability of a third event and do not directly affect each other, then initially (when it has not been ...

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