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	~~'''~~Estimation''' is a mathematical principle used in statistics and data analysis. It involves approximating a quantity of interest that cannot be directly measured, using data that are observed in the process. The process of estimation involves the use of statistical models and methods to make inferences about the population parameters based on a sample of data.		== Estimation ==

	~~== Definition ==~~		[[File:Candy_corn_contest_jar.jpg\|thumb\|right\|A jar filled with candy corn, often used in estimation contests.]]

	~~In statistics~~, an ~~'''estimator'''~~ is a ~~rule for calculating an estimate of a given quantity based on observed data: thus the rule~~, ~~the quantity of interest~~ and ~~its result~~ are ~~distinguished~~.		Estimation is a fundamental skill in mathematics and science, involving the process of finding an approximate value that is reasonably close to the actual value. It is a critical component in various fields, including engineering, physics, and everyday life, where exact numbers are not always necessary or possible to obtain.

	~~There are two types~~ of estimators: point estimators and interval estimators. A '''point estimator''' yields single-valued results (although this includes vectors and other mathematical objects), while an '''interval estimator''' yields a range of plausible values (an interval estimate).		== Importance of Estimation ==

	~~== Methods of~~ Estimation ==		Estimation is important for several reasons:

	~~There are several methods of estimation that can be used, depending on the nature of the~~ data ~~and~~ the ~~quantity~~ of ~~interest~~. ~~Some of the most common methods include:~~		* '''Efficiency''': It allows for quick calculations when precision is not required.
			* '''Decision Making''': Helps in making informed decisions when exact data is unavailable.
			* '''Error Checking''': Provides a way to check the plausibility of results obtained from more precise calculations.

	* [[Maximum likelihood estimation]]		== Techniques of Estimation ==
	* [[Method of ~~moments (statistics)\|Method of moments]]~~
	* [[Bayesian estimation]]
	* [[Least squares]]
	* [[Minimax estimation]]

	~~== Applications ==~~		There are several techniques used in estimation, including:

	Estimation ~~is used in~~ a ~~wide variety of fields, including~~:		* '''Rounding''': Simplifying numbers to the nearest ten, hundred, etc., to make calculations easier.
			* '''Front-end Estimation''': Using the leading digits of a number to make an estimate.
			* '''Clustering''': Grouping numbers that are close in value to simplify calculations.

	* [[Economics]]		== Applications of Estimation ==
	* [[Engineering]]
	* [[Medicine]]
	* [[Social sciences]]
	* [[Physics]]

	~~== See Also ==~~		Estimation is used in various real-world applications:

	* ~~[[Estimation theory]]~~		* '''Construction''': Estimating the amount of materials needed for a project.
	* [[Estimator]]		* '''Finance''': Estimating future expenses or revenues.
	* [[Bias of ~~an estimator]]~~		* '''Science''': Estimating measurements in experiments where precision instruments are not available.
	* ~~[[Variance]]~~
	* ~~[[Standard error]]~~

	== ~~References~~ ==		== Estimation in Education ==

	~~<references />~~		In educational settings, estimation is taught as a part of the mathematics curriculum. It helps students develop number sense and understand the magnitude of numbers. Estimation contests, such as guessing the number of candies in a jar, are popular activities that engage students in practical estimation exercises.

	~~{{stub}}~~		== Related pages ==

	[[~~Category:Statistics~~]]		* [[Approximation]]
	[[~~Category:Mathematical and quantitative methods (economics)~~]]		* [[Mathematics]]
	[[Category:~~Estimation theory~~]]		* [[Measurement]]
			* [[Number sense]]

			[[Category:Mathematics]]

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'''Estimation''' is a mathematical principle used in statistics and data analysis. It involves approximating a quantity of interest that cannot be directly measured, using data that are observed in the process. The process of estimation involves the use of statistical models and methods to make inferences about the population parameters based on a sample of data.

== Definition ==

In statistics, an '''estimator''' is a rule for calculating an estimate of a given quantity based on observed data: thus the rule, the quantity of interest and its result are distinguished.

There are two types of estimators: point estimators and interval estimators. A '''point estimator''' yields single-valued results (although this includes vectors and other mathematical objects), while an '''interval estimator''' yields a range of plausible values (an interval estimate).

== Methods of Estimation ==

There are several methods of estimation that can be used, depending on the nature of the data and the quantity of interest. Some of the most common methods include:

* [[Maximum likelihood estimation]]
* [[Method of moments (statistics)|Method of moments]]
* [[Bayesian estimation]]
* [[Least squares]]
* [[Minimax estimation]]

== Applications ==

Estimation is used in a wide variety of fields, including:

* [[Economics]]
* [[Engineering]]
* [[Medicine]]
* [[Social sciences]]
* [[Physics]]

== See Also ==

* [[Estimation theory]]
* [[Estimator]]
* [[Bias of an estimator]]
* [[Variance]]
* [[Standard error]]

== References ==

<references />

{{stub}}

[[Category:Statistics]]
[[Category:Mathematical and quantitative methods (economics)]]
[[Category:Estimation theory]]

Estimation - Revision history

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