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| | An underweight person could have low immunity, reduced endurance, plus a deficiency of vitamins inside his body. So, weight control is important. There are numerous methods to determine the perfect fat of the person. Among them are, waist to height ratio, and height to weight ratio.<br><br>The difference inside the obese group is likely to be muscle. Folks with more muscle are more fit and healthy, yet that muscle puts them in the obese group for their height. Numbers that receive tossed about frequently are which 60% of Americans are obese plus half of those are overweight. These numbers are based strictly off the BMI, plus the group of obese Americans is likely to be much lower.<br><br>Examples 1 and 2 show that an exponent of 3 is a bit more realistic than 2 for estimating the weight of the person for a given height. With all due modesty, I propose the Larry Index (LI) as a reasonable compromise, plus as a realistic alternative to Ancel Keys' BMI.<br><br>Knowing your BMI via the [http://safedietplans.com/bmi-calculator bmi calculator females] female a female may get a greater control over her body, fat and looks. She may feel more confident whether or not she would not possess the perfect vital statistics. A girl, especially whenever she is pregnant or is feeding her baby, must ignore her BMI though. At the same time, some amount of body fat in a woman's body really helps her reproductive system. If a woman has body fat that is lower than twenty percent, can even have irregular periods plus difficulties conceiving a child. Body fat, whenever not inside excess, assists ladies to fight against osteoporosis.<br><br>There are many fast and easy online tools to employ your individual BMI, but basically it really is a calculation of the current weight against the height. A 'normal' range of BMI is estimated to be between 18.5 and 24.9. A survey conducted inside 1994 indicated that over 59% of American men plus 49% of American ladies were over 25%. A 2007 study today states that 63% of individuals are today over 25%. That is a startling statistic plus certainly one which indicates which losing fat is much more critical than ever because that trend should be reduced.<br><br>The 3 Day Cardiac Diet has set menu plans for breakfast, lunch and dinner for 3 days. Every day is limited to about 800 calories. While several claim which there is a specialized "chemical reaction," much of the fat loss benefit is probably obtained by the limited calorie intake. Also, there are really few carbs found on the diet that leads to water loss.<br><br>If BMI is not the proper tool, what is? Well, to truly precisely tell what percent of the fat is fat, you must be weighed underwater. That's a hassle, not the sort of thing the average person can do, absolutely not regularly. But, with just a tape measure, you can calculate a waist-hip ratio. Next you are able to employ http://www.healthcalculators.org/calculators/waist_hip.asp to see when it's in a healthy range. This really is a much more sensible measure. |
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| {{Use dmy dates|date=June 2013}}
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| In [[mathematics]] and [[statistics]], the '''arithmetic mean''' ({{IPAc-en|pron|ˌ|æ|r|ɪ|θ|ˈ|m|ɛ|t|ɪ|k|_|ˈ|m|iː|n}}), or simply the [[mean]] or '''average''' when the context is clear, is the sum of a collection of numbers divided by the number of numbers in the collection.<ref>{{cite book | last = Jacobs | first = Harold R. | title = Mathematics: A Human Endeavor | edition = Third | year = 1994 | publisher = [[W. H. Freeman]] | page = 547 | isbn = 0-7167-2426-X}}</ref> The collection is often a set of results of an [[experiment (probability theory)|experiment]], or a set of results from a [[Survey methodology|survey]]. The term "arithmetic mean" is preferred in some contexts in mathematics and statistics because it helps distinguish it from other [[average|mean]]s such as the [[geometric mean]] and the [[harmonic mean]].
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| In addition to mathematics and statistics, the arithmetic mean is used frequently in fields such as economics, [[sociology]], and history, and it is used in almost every academic field to some extent. For example, per capita income is the arithmetic average income of a nation's population.
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| While the arithmetic mean is often used to report [[central tendency|central tendencies]], it is not a [[robust statistic]], meaning that it is greatly influenced by [[outlier]]s (values that are very much larger or smaller than most of the values). Notably, for [[skewed distribution]]s, such as the [[distribution of income]] for which a few people's incomes are substantially greater than most people's, the arithmetic mean may not accord with one's notion of "middle", and robust statistics such as the [[median]] may be a better description of central tendency.
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| In a more obscure usage, any sequence of values that form an [[Arithmetic progression|arithmetic sequence]] between two numbers ''x'' and ''y'' can be called "arithmetic means between ''x'' and ''y''."<ref>{{cite book | last = Foerster | first = Paul A. | title = Algebra and Trigonometry: Functions and Applications, Teacher's Edition | edition = Classics | year = 2006 | publisher = [[Prentice Hall]] | location = Upper Saddle River, NJ | page = 573 | url = http://www.amazon.com/Algebra-Trigonometry-Functions-Applications-Prentice/dp/0131657100 | isbn = 0-13-165711-9}}</ref>
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| ==Definition==
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| Suppose we have a data set containing the values <math>a_1,\ldots,a_n.</math> The arithmetic mean <math>A</math> is defined by the formula
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| :<math>A=\frac{1}{n}\sum_{i=1}^{n} a_i</math>.
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| If the data set is a [[statistical population]] (i.e., consists of every possible observation and not just a subset of them), then the mean of that population is called the '''population mean'''. If the data set is a [[sampling (statistics)|statistical sample]] (a subset of the population) we call the statistic resulting from this calculation a '''sample mean'''.
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| The arithmetic mean of a variable is often denoted by a bar, for example as in <math>\bar{x}</math> (read "x bar"), which is the mean of the <math>n</math> values <math>x_1,x_2,\ldots,x_n</math>.<ref name="JM">{{cite book| last = Medhi| first = Jyotiprasad| title = Statistical Methods: An Introductory Text| url = http://books.google.com/?id=bRUwgf_q5RsC| year = 1992| publisher = New Age International| isbn = 9788122404197| pages = 53–58 }}</ref>
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| ==Motivating properties==
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| The arithmetic mean has several properties that make it useful, especially as a measure of central tendency. These include:
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| * If numbers <math>x_1,\dotsc,x_n</math> have mean <math>\bar{x}</math>, then <math>(x_1-\bar{x}) + \dotsb + (x_n-\bar{x}) = 0</math>. Since <math>x_i-\bar{x}</math> is the distance from a given number to the mean, one way to interpret this property is as saying that the numbers to the left of the mean are balanced by the numbers to the right of the mean. The mean is the only single number for which the [[errors and residuals in statistics|residuals]] (deviations from the estimate) sum to zero.
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| * If it is required to use a single number as a "typical" value for a set of known numbers <math>x_1,\dotsc,x_n</math>, then the arithmetic mean of the numbers does this best, in the sense of minimizing the sum of squared deviations from the typical value: the sum of <math>(x_i-\bar{x})^2</math>. (It follows that the sample mean is also the best single predictor in the sense of having the lowest [[root mean squared error]].)<ref name="JM"/> If the arithmetic mean of a population of numbers is desired, then the estimate of it that is [[unbiased estimate|unbiased]] is the arithmetic mean of a sample drawn from the population.
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| ==Contrast with median==
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| The arithmetic mean may be contrasted with the median. The median is defined such that half the values are larger than, and half are smaller than, the median. If elements in the sample data [[arithmetic progression|increase arithmetically]], when placed in some order, then the median and arithmetic average are equal. For example, consider the data sample <math>{1,2,3,4}</math>. The average is <math>2.5</math>, as is the median. However, when we consider a sample that cannot be arranged so as to increase arithmetically, such as <math>{1,2,4,8,16}</math>, the median and arithmetic average can differ significantly. In this case the arithmetic average is 6.2 and the median is 4. In general the average value can vary significantly from most values in the sample, and can be larger or smaller than most of them.
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| There are applications of this phenomenon in many fields. For example, since the 1980s in the United States median income has increased more slowly than the arithmetic average of income.
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| ==Generalizations==
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| ===Weighted average===
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| A [[weighted average]] or weighted mean is an average in which some data points count more strongly than others, in that they are given more weight in the calculation. For example, the arithmetic mean of <math>3</math> and <math>5</math> is <math>\frac{(3+5)}{2} = 4</math>, or equivalently <math>\left( \frac{1}{2} \cdot 3\right) + \left( \frac{1}{2} \cdot 5\right) = 4</math>. In contrast, a ''weighted'' mean in which the first number receives twice as much weight as the second (perhaps because it is assumed to appear twice as often in the general population from which these numbers were sampled) would be calculated as <math>\left( \frac{2}{3} \cdot 3\right) + \left(\frac{1}{3} \cdot 5\right) = \frac{11}{3}</math>. Here the weights, which necessarily sum to the value one, are <math>(2/3)</math> and <math>(1/3)</math>, the former being twice the latter. Note that the arithmetic mean (sometimes called the "unweighted average" or "equally weighted average") can be interpreted as a special case of a weighted average in which all the weights are equal to each other (equal to <math>\frac{1}{2}</math> in the above example, and equal to <math>\frac{1}{n}</math> in a situation with <math>n</math> numbers being averaged).
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| ===Continuous probability distributions===
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| [[File:Comparison mean median mode.svg|thumb|300px|Comparison of mean, [[median]] and [[mode (statistics)|mode]] of two [[log-normal distribution]]s with different [[skewness]].]]
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| When a population of numbers, and any sample of data from it, could take on any of a continuous range of numbers, instead of for example just integers, then the [[probability]] of a number falling into one range of possible values could differ from the probability of falling into a different range of possible values, even if the lengths of both ranges are the same. In such a case the set of probabilities can be described using a [[continuous probability distribution]]. The analog of a weighted average in this context, in which there are an infinitude of possibilities for the precise value of the variable, is called the ''mean of the probability distribution''. The most widely encountered probability distribution is called the [[normal distribution]]; it has the property that all measures of its central tendency, including not just the mean but also the aforementioned median and the [[Mode (statistics)|mode]], are equal to each other. This property does not hold however, in the cases of a great many probability distributions, such as the [[lognormal distribution]] illustrated here.
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| ==Angles==
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| {{Main|Mean of circular quantities}}
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| Particular care must be taken when using cyclic data such as phases or [[angle]]s. Naïvely taking the arithmetic mean of 1° and 359° yields a result of 180°.
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| This is incorrect for two reasons:
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| * Firstly, angle measurements are only defined up to an additive constant of [[degree (angle)|360°]] (or 2π, if measuring in [[radian]]s). Thus one could as easily call these 1° and −1°, or 361° and 719°, each of which gives a different average.
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| * Secondly, in this situation, 0° (equivalently, 360°) is geometrically a better ''average'' value: there is lower [[statistical dispersion|dispersion]] about it (the points are both 1° from it, and 179° from 180°, the putative average).
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| In general application such an oversight will lead to the average value artificially moving towards the middle of the numerical range. A solution to this problem is to use the optimization formulation ([[viz.]], define the mean as the central point: the point about which one has the lowest dispersion), and redefine the difference as a modular distance (i.e., the distance on the circle: so the modular distance between 1° and 359° is 2°, not 358°).
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| ==See also==
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| * [[Average]]
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| * [[Fréchet mean]]
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| * [[Generalized mean]]
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| * [[Geometric mean]]
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| * [[Mode (statistics)|Mode]]
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| * [[Sample mean and covariance]]
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| * [[Summary statistics]]
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| ==References==
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| {{reflist}}
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| ==Further reading==
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| * {{cite book| last = Huff| first = Darrell| title = How to Lie with Statistics| year = 1993| publisher = W. W. Norton| isbn = 978-0-393-31072-6 }}
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| ==External links==
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| * [http://www.sengpielaudio.com/calculator-geommean.htm Calculations and comparisons between arithmetic and geometric mean of two numbers]
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| * {{MathWorld | urlname= ArithmeticMean | title= Arithmetic Mean}}
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| {{Statistics|descriptive}}
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| {{Portal bar|Statistics}}
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| {{DEFAULTSORT:Arithmetic Mean}}
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| [[Category:Means]]
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| [[it:Media (statistica)#Media aritmetica]]
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An underweight person could have low immunity, reduced endurance, plus a deficiency of vitamins inside his body. So, weight control is important. There are numerous methods to determine the perfect fat of the person. Among them are, waist to height ratio, and height to weight ratio.
The difference inside the obese group is likely to be muscle. Folks with more muscle are more fit and healthy, yet that muscle puts them in the obese group for their height. Numbers that receive tossed about frequently are which 60% of Americans are obese plus half of those are overweight. These numbers are based strictly off the BMI, plus the group of obese Americans is likely to be much lower.
Examples 1 and 2 show that an exponent of 3 is a bit more realistic than 2 for estimating the weight of the person for a given height. With all due modesty, I propose the Larry Index (LI) as a reasonable compromise, plus as a realistic alternative to Ancel Keys' BMI.
Knowing your BMI via the bmi calculator females female a female may get a greater control over her body, fat and looks. She may feel more confident whether or not she would not possess the perfect vital statistics. A girl, especially whenever she is pregnant or is feeding her baby, must ignore her BMI though. At the same time, some amount of body fat in a woman's body really helps her reproductive system. If a woman has body fat that is lower than twenty percent, can even have irregular periods plus difficulties conceiving a child. Body fat, whenever not inside excess, assists ladies to fight against osteoporosis.
There are many fast and easy online tools to employ your individual BMI, but basically it really is a calculation of the current weight against the height. A 'normal' range of BMI is estimated to be between 18.5 and 24.9. A survey conducted inside 1994 indicated that over 59% of American men plus 49% of American ladies were over 25%. A 2007 study today states that 63% of individuals are today over 25%. That is a startling statistic plus certainly one which indicates which losing fat is much more critical than ever because that trend should be reduced.
The 3 Day Cardiac Diet has set menu plans for breakfast, lunch and dinner for 3 days. Every day is limited to about 800 calories. While several claim which there is a specialized "chemical reaction," much of the fat loss benefit is probably obtained by the limited calorie intake. Also, there are really few carbs found on the diet that leads to water loss.
If BMI is not the proper tool, what is? Well, to truly precisely tell what percent of the fat is fat, you must be weighed underwater. That's a hassle, not the sort of thing the average person can do, absolutely not regularly. But, with just a tape measure, you can calculate a waist-hip ratio. Next you are able to employ http://www.healthcalculators.org/calculators/waist_hip.asp to see when it's in a healthy range. This really is a much more sensible measure.