what are deviations in statistics?
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In mathematics and statistics, deviation is a measure of difference between the observed value of a variable and some other value, often that variable's mean. The sign of the deviation reports the direction of that difference (the deviation is positive when the observed value exceeds the reference value).
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The standard deviation measures the spread of the data about the mean value. It is useful in comparing sets of data which may have the same mean but a different range. For example, the mean of the following two is the same: 15, 15, 15, 14, 16 and 2, 7, 14, 22, 30. However, the second is clearly more spread out.
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Standard deviation is a number used to tell how measurements for a group are spread out from the average (mean or expected value). ... Standard deviation is also useful in money, where the standard deviation on interest earned shows how different one person's interest earned might be from the average.
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['Standard deviation looks at how spread out a group of numbers is from the mean, by looking at the square root of the variance.', 'The variance measures the average degree to which each point differs from the mean—the average of all data points.']
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Statistics » Mean deviation from the mean The mean deviation from the mean is a measure of spread. It tells you how far the values deviate from the mean. Remember that the deviation always is a positive number.
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['Standard deviation is only used to measure spread or dispersion around the mean of a data set.', 'Standard deviation is never negative.', 'Standard deviation is sensitive to outliers. ... ', 'For data with approximately the same mean, the greater the spread, the greater the standard deviation.']
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Standard Deviation is a measure of the variability of a data set. This is a standard statistical measure. See, for example: Standard Deviation entry at Wikipedia. JMeter calculates the population standard deviation (e.g. STDEVP function in spreadsheets), not the sample standard deviation (e.g. STDEV).
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['Calculate the deviation of each measurement. ... ', 'Calculate the squares of each of the deviations (i.e. di2). ... ', 'Add together all the squares of the deviations i.e.', 'Divide by the total number of measurements (i.e. n) to obtain the mean of all the square deviations.']
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A useful property of the standard deviation is that, unlike the variance, it is expressed in the same units as the data. In addition to expressing the variability of a population, the standard deviation is commonly used to measure confidence in statistical conclusions.
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Standard deviation is a statistical measurement in finance that, when applied to the annual rate of return of an investment, sheds light on that investment's historical volatility. ... For example, a volatile stock has a high standard deviation, while the deviation of a stable blue-chip stock is usually rather low.
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Standard deviation is the deviation from the mean, and a standard deviation is nothing but the square root of the variance. Mean is an average of all set of data available with an investor or company. Standard deviation used for measuring the volatility of a stock.
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Variance (σ2) in statistics is a measurement of the spread between numbers in a data set. That is, it measures how far each number in the set is from the mean and therefore from every other number in the set.
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A standard deviation is a measurement used to quantify the variability of data dispersion, in a set of given values around the mean. The mean, in turn, refers to the average of all data points in the data set or sequence and will be found at the highest point on the bell curve.
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The standard deviation is the square root of the average of the squared deviations from the mean, i.e., std = sqrt(mean(abs(x - x. mean())**2)) . The average squared deviation is normally calculated as x. sum() / N , where N = len(x) .
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The Standard Deviation is a measure of how spread out numbers are. ... The symbol for Standard Deviation is σ (the Greek letter sigma).
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The standard deviation (abbreviated s or SD) is calculated according to the following formula: That is, calculate the deviation from the mean for each point, square those results, sum them, divide by the number of points minus one, and finally take the square root.
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Standard deviation measures how much variance there is in a set of numbers compared to the average (mean) of the numbers. The STDEV function is meant to estimate standard deviation in a sample. If data represents an entire population, use the STDEVP function.