సరాసరి పేజీ సోర్సు చూడండి

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సరాసరిను [[సగటు]] అని కూడా అంటారు. ఆంగ్ల భాషలో ఏవరేజ్ (average) అని అంటారు.
సరాసరిని లెక్కించడానికి [[సూత్రము]]
''n'' మొత్తములో సంఖ్యలుంటే , ai ప్రతి సంఖ్యా పోలును, ఇందులో i=1,2...n.<br />
ప్రతి సంఖ్యను కూడి, వాటిని మొత్తముతో భాగించాల.
సరాసరి=[(a1+a2+....+an)÷n]
<br />
ఉదాహరణముగా ఈ ప్రశ్నను తీసుకొందాం : 
ముగ్గురు మిత్రులలో ఒక్కడు నెలకు రూ.10,000, రెండవ వ్యక్తి రూ.20,000, మూడవ వ్యక్తి రూ.30,000 సంపాదిస్తున్నారు. అప్పుడు నెలకు వారి సగటు ఆదాయము ఎంత?
జవాబు: ఇక్కడ మొత్తం మూడు సంఖ్యలున్నయి.
 అంటే n =3,
మరియు i=1..n
అప్పుడు a1=10,000; a2=20,000;a3=30,000<br />
a1+a2+a3=10,000+20,000+30,000=60,000.<br />
ఇప్పుడు సరాసరి=(60,000)/(3)=20,000<br />
అనగా ఆ ముగ్గురు మిత్రుల యొక్క ఒకనెల సరాసరి ఆదాయము రూ.20,000-->
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వ్యవహారిక భాషలో "సరాసరి" అనునది రాశుల మొత్తము ను రాశుల సంఖ్యచేభాగించగా వచ్చు భాగఫలము. మరో విధంగా చెప్పాలంటె యిది "అంక మధ్యమం" అవుతుంది. అయితే "సరాసరి" ని మరో విధంగా "మధ్యగతము", "బహుళకము" లేదా యితర మధ్యస్థ లేదా సగటు విలువగా తీసుకోవచ్చు. [[సాంఖ్యక శాస్త్రం]] లో యీ పదాలన్నింటినీ "కేంద్రీయ ప్రవృత్తి మానాలు" అని పిలుస్తారు. [[గణిత శాస్త్రము]] లో "సరాసరి" యొక్క భావన వివిధ రకాలుగా విస్తరించబడినది. కాని అనేక సందర్భాలలో దీనిని "అంక మధ్యమం" గా తీసుకుంటారు.
==గణన==
===పైథాగొరియన్ అర్థం===
పైథోగొరియన్ అర్థం ప్రకారం సాధారణంగా సరాసరి అనునది - అంకమధ్యమం, గుణ మధ్యమం, హరాత్మక మధ్యమం.


====అంక మధ్యమం====
{{Main|అంక మధ్యమం}}
ఒక దత్తాంశములో ''n'' సంఖ్యలు ఉన్నప్పుడు ప్రతి సంఖ్యను ''a<sub>i</sub>'',(''i''&nbsp;=&nbsp;1,&nbsp;…,&nbsp;''n'', అయితే), అంకమధ్యమం అనగా ''a<sub>i</sub>ల'' మొత్తం ను ''n'' చే భాగించగా వచ్చు భాగఫలము. లేదా 
:<math>AM = \frac{1}{n}\sum_{i=1}^na_i = \frac{1}{n}\left(a_1 + a_2 + \cdots + a_n\right)</math>

The arithmetic mean, often simply called the mean, of two numbers, such as 2 and 8, is obtained by finding a value A such that 2 + 8 = A + A. One may find that ''A'' =&nbsp;(2&nbsp;+&nbsp;8)/2 =&nbsp;5. Switching the order of 2 and 8 to read 8 and 2 does not change the resulting value obtained for A. The mean 5 is not less than the minimum 2 nor greater than the maximum&nbsp;8. If we increase the number of terms in the list for which we want an average, we get, for example, that the arithmetic mean of 2, 8, and 11 is found by solving for the value of ''A'' in the equation 2&nbsp;+&nbsp;8&nbsp;+&nbsp;11 =&nbsp;''A''&nbsp;+&nbsp;''A''&nbsp;+&nbsp;''A''. One finds that ''A'' =&nbsp;(2&nbsp;+&nbsp;8&nbsp;+&nbsp;11)/3 =&nbsp;7.

====గుణ మధ్యమం====
The [[geometric mean]] of ''n'' non-negative numbers is obtained by multiplying them all together and then taking the ''n''th root. In algebraic terms, the geometric mean of ''a''<sub>1</sub>,&nbsp;''a''<sub>2</sub>,&nbsp;…,&nbsp;''a''<sub>''n''</sub> is defined as

: <math>\text{GM=} \sqrt[n]{\prod_{i=1}^n a_i} = \sqrt[n]{a_1 a_2 \cdots a_n}</math>

Geometric mean can be thought of as the [[antilog]] of the arithmetic mean of the [[logarithm|logs]] of the numbers.

Example: Geometric mean of 2 and 8 is <math>GM = \sqrt{2 \cdot 8} = 4</math>

====హరాత్మక మధ్యమం====
[[Harmonic mean]] for a non-empty collection of numbers ''a''<sub>1</sub>,&nbsp;''a''<sub>2</sub>,&nbsp;…,&nbsp;''a''<sub>''n''</sub>, all different from 0, is defined as the reciprocal of the arithmetic mean of the reciprocals of the ''a''<sub>''i''</sub>{{'}}s:

: <math>HM = \frac{1}{\frac{1}{n}\sum_{i=1}^n \frac{1}{a_i}} = \frac{n}{\frac{1}{a_1} + \frac{1}{a_2} + \cdots + \frac{1}{a_n}}</math>

One example where it is useful is calculating the average speed for a number of fixed-distance trips. For example, if the speed for going from point ''A'' to ''B'' was 60&nbsp;km/h, and the speed for returning from ''B'' to ''A'' was 40&nbsp;km/h, then the average speed is given by

: <math>\frac{2}{\frac{1}{60} + \frac{1}{40}} = 48</math>

====AM, GM, HM ల మధ్య సంబంధం====
A well known inequality concerning arithmetic, geometric, and harmonic means for any set of positive numbers is

: <math>AM \ge GM \ge HM</math>

It is easy to remember noting that the alphabetical order of the letters ''A'', ''G'', and ''H'' is preserved in the inequality. See [[Inequality of arithmetic and geometric means]].

===బహుళకము===
[[Image:Comparison mean median mode.svg|thumb|300px|Comparison of [[mean|arithmetic mean]], [[median]] and [[mode (statistics)|mode]] of two [[log-normal distribution]]s with different [[skewness]].]]
{{Main|Mode (statistics)}}
The most frequently occurring number in a list is called the mode. For example, the mode of the list (1, 2, 2, 3, 3, 3, 4) is 3. The mode is not necessarily uniquely defined; for example, the list (1, 2, 2, 3, 3, 5) has the two modes 2 and 3. The mode is more meaningful and potentially useful if there are many numbers in the list, and the frequency of the numbers progresses smoothly (e.g., if out of a group of 1,000 people, 30 people weigh 61&nbsp;kg, 32 weigh 62&nbsp;kg, 29 weigh 63&nbsp;kg, and all the other possible weights occur less frequently, then 62&nbsp;kg is the mode).

The mode has the advantage that it can be used with non-numerical data (e.g., red cars are most frequent), while other averages cannot.

===మధ్యగతం===
{{Main|మధ్యగతం}}
The median is the middle number of the group when they are ranked in order. (If there are an even number of numbers, the mean of the middle two is taken.) 

Thus to find the median, order the list according to its elements' magnitude and then repeatedly remove the pair consisting of the highest and lowest values until either one or two values are left. If exactly one value is left, it is the median; if two values, the median is the arithmetic mean of these two. This method takes the list 1, 7, 3, 13 and orders it to read 1, 3, 7, 13. Then the 1 and 13 are removed to obtain the list 3, 7. Since there are two elements in this remaining list, the median is their arithmetic mean, (3 + 7)/2 = 5.

==సారాంశం రకాలు==

The [[table of mathematical symbols]] explains the symbols used below. 
{|class="wikitable" style="background:white;"
|-
! Name !! Equation or description
|-
| [[Arithmetic mean]] || <math>\bar{x} = \frac{1}{n}\sum_{i=1}^n x_i = \frac{1}{n} (x_1 + \cdots + x_n)</math>
|-
| [[Median]] || The middle value that separates the higher half from the lower half of the data set
|-
| [[Geometric median]] || A [[rotation (mathematics)|rotation]] [[invariant (mathematics)|invariant]] extension of the [[median]] for points in R<sup>n</sup>
|-
| [[Mode (statistics)|Mode]] || The most frequent value in the data set
|-
| [[Geometric mean]] || <math>\bigg(\prod_{i=1}^n x_i \bigg)^{\frac{1}{n}} = \sqrt[n]{x_1 \cdot x_2 \dotsb x_n}</math>
|-
| [[Harmonic mean]] || <math>\frac{n}{\frac{1}{x_1} + \frac{1}{x_2} + \cdots + \frac{1}{x_n}}</math>
|-
| [[Quadratic mean]]<br />(or RMS) || <math>\sqrt{\frac{1}{n} \sum_{i=1}^{n} x_i^2} = \sqrt{\frac{1}{n}\left(x_1^2 + x_2^2 + \cdots + x_n^2\right)}</math>
|-
| [[Generalized mean]] || <math>\sqrt[p]{\frac{1}{n} \cdot \sum_{i=1}^n x_{i}^p}</math>
|-
| [[Weighted mean]] || <math>\frac{ \sum_{i=1}^n w_i x_i}{\sum_{i=1}^n w_i} = \frac{w_1 x_1 + w_2 x_2 + \cdots + w_n x_n}{w_1 + w_2 + \cdots + w_n}</math>
|-
| [[Truncated mean]] || The arithmetic mean of data values after a certain number or proportion of the highest and lowest data values have been discarded
|-
| [[Interquartile mean]] || A special case of the truncated mean, using the [[interquartile range]]
|-
| [[Midrange]] || <math>\frac{1}{2}\left(\max x + \min x\right)</math>
|-
| [[Winsorized mean]] || Similar to the truncated mean, but, rather than deleting the extreme values, they are set equal to the largest and smallest values that remain
|-
| [[Compound annual growth rate|Annualization]] || <math> {\left[ \prod (1 + R_i )^{t_i} \right] }^{\frac{1}{\sum t_i}} - 1</math>
|}

==యితర రకాలు==

Other more sophisticated averages are: [[trimean]], [[trimedian]], and [[normalized mean]], with their generalizations.<ref>{{cite journal |last1=Merigo |first1=Jose M. |last2=Cananovas |first2=Montserrat |title=The Generalized Hybrid Averaging Operator and its Application in Decision Making |year=2009 |journal=Journal of Quantitative Methods for Economics and Business Administration |volume=9 |pages=69–84 |issn=1886-516X |url=http://www.upo.es/RevMetCuant/art.php?id=38 }}{{Dead link|date=జనవరి 2020 |bot=InternetArchiveBot |fix-attempted=yes }}</ref>

One can create one's own average metric using the [[generalized f-mean|generalized ''f''-mean]]:

: <math>y = f^{-1}\left(\frac{1}{n}\left[f(x_1) + f(x_2) + \cdots + f(x_n)\right]\right)</math>

where ''f'' is any invertible function. The harmonic mean is an example of this using ''f''(''x'') = 1/''x'', and the geometric mean is another, using ''f''(''x'') = log&nbsp;''x''. 

However, this method for generating means is not general enough to capture all averages. A more general method<ref name=Bibby/> for defining an average takes any function ''g''(''x''<sub>1</sub>,&nbsp;''x''<sub>2</sub>,&nbsp;…,&nbsp;''x''<sub>''n''</sub>) of a list of arguments that is [[Continuous function|continuous]], [[Monotonicity|strictly increasing]] in each argument, and symmetric (invariant under [[permutation]] of the arguments). The average ''y'' is then the value that, when replacing each member of the list, results in the same function value: {{nowrap|1=''g''(''y'', ''y'', …, ''y'') =}} {{nowrap|''g''(''x''<sub>1</sub>, ''x''<sub>2</sub>, …, ''x''<sub>''n''</sub>)}}. This most general definition still captures the important property of all averages that the average of a list of identical elements is that element itself. The function {{nowrap|1=''g''(''x''<sub>1</sub>, ''x''<sub>2</sub>, …, ''x''<sub>''n''</sub>) =}} {{nowrap|''x''<sub>1</sub>+''x''<sub>2</sub>+ ··· + ''x''<sub>''n''</sub>}} provides the arithmetic mean. The function {{nowrap|1 = ''g''(''x''<sub>1</sub>, ''x''<sub>2</sub>, …, ''x''<sub>''n''</sub>) =}} {{nowrap|''x''<sub>1</sub>''x''<sub>2</sub>···''x''<sub>''n''</sub>}} (where the list elements are positive numbers) provides the geometric mean. The function {{nowrap|1 = ''g''(''x''<sub>1</sub>, ''x''<sub>2</sub>, …, ''x''<sub>''n''</sub>) =}} {{nowrap|−(''x''<sub>1</sub><sup>−1</sup>+''x''<sub>2</sub><sup>−1</sup>+ ··· + ''x''<sub>''n''</sub><sup>−1</sup>)}} (where the list elements are positive numbers) provides the harmonic mean.<ref name=Bibby>John Bibby (1974). “Axiomatisations of the average and a further generalisation of monotonic sequences”. ''[[Glasgow Mathematical Journal]]'', vol. 15, pp.&nbsp;63–65.</ref>

===Average percentage return and CAGR===
{{Main|Compound annual growth rate}}
A type of average used in finance is the average percentage return. It is an example of a geometric mean. When the returns are annual, it is called the Compound Annual Growth Rate (CAGR). For example, if we are considering a period of two years, and the investment return in the first year is −10% and the return in the second year is +60%, then the average percentage return or CAGR, ''R'', can be obtained by solving the equation: {{nowrap|1= (1 − 10%) × (1 + 60%) = (1 − 0.1) × (1 + 0.6) = (1 + ''R'') × (1 + ''R'')}}. The value of ''R'' that makes this equation true is 0.2, or 20%. This means that the total return over the 2-year period is the same as if there had been 20% growth each year. Note that the order of the years makes no difference – the average percentage returns of +60% and −10% is the same result as that for −10% and +60%. 

This method can be generalized to examples in which the periods are not equal. For example, consider a period of a half of a year for which the return is −23% and a period of two and a half years for which the return is +13%. The average percentage return for the combined period is the single year return, ''R'', that is the solution of the following equation: {{nowrap|1= (1 − 0.23)<sup>0.5</sup> × (1 + 0.13)<sup>2.5</sup> = (1 + ''R'')<sup>0.5+2.5</sup>}}, giving an average percentage return ''R'' of 0.0600 or 6.00%.

==In data streams==
{{move section portions|Algorithms for calculating variance#Online algorithm|date=April 2013}}
The concept of an average can be applied to a stream of data as well as a bounded set, the goal being to find a value that recent data clusters about in some way. The stream may be distributed in time, as in samples taken by some data acquisition system from which we want to remove noise, or in space, as in pixels in an image from which we want to extract some property. An easy-to-understand and widely used application of average to a stream is the simple [[moving average]] in which we compute the arithmetic mean of the most recent N data items in the stream. To advance one position in the stream, we add 1/N times the new data item and subtract 1/N times the data item N places back in the stream.

:Update rule for a window of size <math>k</math> upon seeing new element <math>x_n</math>:
<center><math>\mu_{n, {n - k}} = \mu_{n - 1, n - k - 1} + \frac{x_n}{k} - \frac{x_{n - k - 1}}{k}</math></center>

==Etymology==
"Few words have received more etymological investigation." <ref>Oxford English Dictionary </ref> In the 16th century ''average'' meant a customs duty, or the like, and was used in the Mediterranean area. It came to mean the cost of damage sustained at sea. From that came an "average adjuster" who decided how to apportion a loss between the owners and insurers of a ship and cargo. 

Marine damage is either ''particular average'', which is borne only by the owner of the damaged property, or [[general average]], where the owner can claim a proportional contribution from all the parties to the marine venture. The type of calculations used in adjusting general average gave rise to the use of "average" to mean "arithmetic mean".

The root is found in Arabic as ''awar'', in Italian as ''avaria'', in French as ''avarie'' and in Dutch as ''averij''. It is unclear in which language the word first appeared.

There is earlier (from at least the 11th century), unrelated use of the word. It appears to be an old legal term for a tenant's day labour obligation to a sheriff, probably anglicised from "avera" found in the English [[Domesday Book]] (1085).

==యివి కూడా చూడండి==
{{Portal|Statistics}}
*[[Algorithms for calculating variance]]
*[[Law of averages]]
*[[Measures of statistical dispersion]]
*[[Spherical mean]]

==నోట్సు==
{{Reflist}}

==సూచికలు==
*{{Cite book|first1=G.H.|last1=Hardy|authorlink1=G.H. Hardy|first2=J.E.|last2=Littlewood|authorlink2=John Edensor Littlewood|first3=G.|last3=Pólya|authorlink3=George Pólya|title=Inequalities|url=https://archive.org/details/inequalities0000hard_s5h4|year=1988|publisher=Cambridge University Press|edition=2nd|isbn=978-0-521-35880-4|postscript=<!-- Bot inserted parameter. Either remove it; or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}

==యితర లింకులు==
{{Wiktionary}}
*[https://web.archive.org/web/20070810034709/http://economicsbulletin.vanderbilt.edu/2004/volume3/EB-04C10011A.pdf Median as a weighted arithmetic mean of all Sample Observations]
*[http://www.sengpielaudio.com/calculator-geommean.htm Calculations and comparison between arithmetic and geometric mean of two values]

[[Category:సాంఖ్యక శాస్త్రము]]
[[Category:గణిత శాస్త్రము]]
[[Category:Statistical terminology]]
[[Category:అంకగణిత ప్రమేయాలు]]