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The mode of a sample is the element that occurs most often in the collection. For example, the mode of the sample [1, 3, 6, 6, 6, 6, 7, 7, 12, 12, 17] is 6. Given the list of data [1, 1, 2, 4, 4] its mode is not unique. A dataset, in such a case, is said to be bimodal, while a set with more than two modes may be described as multimodal.
This page will attempt to list examples in mathematics. To qualify for inclusion, an article should be about a mathematical object with a fair amount of concreteness. Usually a definition of an abstract concept, a theorem, or a proof would not be an "example" as the term should be understood here (an elegant proof of an isolated but particularly striking fact, as opposed to a proof of a ...
Consider a simple yes/no poll as a sample of respondents drawn from a population , reporting the percentage of yes responses. We would like to know how close p {\displaystyle p} is to the true result of a survey of the entire population N {\displaystyle N} , without having to conduct one.
The term "mode" in this context refers to any peak of the distribution, not just to the strict definition of mode which is usual in statistics. If there is a single mode, the distribution function is called "unimodal". If it has more modes it is "bimodal" (2), "trimodal" (3), etc., or in general, "multimodal". [2]
The code for the math example reads: <math display= "inline" > \sum_{i=0}^\infty 2^{-i} </math> The quotation marks around inline are optional and display=inline is also valid. [2] Technically, the command \textstyle will be added to the user input before the TeX command is passed to the renderer. The result will be displayed without further ...
This can be translated to an answer over , since for any ,,, [] is a mode for [:] if and only if [] is a mode for [:]. We can convert an answer for B {\displaystyle B} to an answer for A {\displaystyle A} in constant time by looking in A {\displaystyle A} or B {\displaystyle B} at the corresponding index.
In statistics, ordinary least squares (OLS) is a type of linear least squares method for choosing the unknown parameters in a linear regression model (with fixed level-one [clarification needed] effects of a linear function of a set of explanatory variables) by the principle of least squares: minimizing the sum of the squares of the differences between the observed dependent variable (values ...
The simplest example given by Thimbleby of a possible problem when using an immediate-execution calculator is 4 × (−5). As a written formula the value of this is −20 because the minus sign is intended to indicate a negative number, rather than a subtraction, and this is the way that it would be interpreted by a formula calculator.
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