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Standard deviation - Wikipedia
https://en.m.wikipedia.org/wiki/Standard_deviation
WEBStandard deviation may be abbreviated SD, and is most commonly represented in mathematical texts and equations by the lower case Greek letter σ (sigma), for the population standard deviation, or the Latin letter s, for the sample standard deviation.
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How to Calculate Standard Deviation (Guide) | Calculator
https://www.scribbr.com/statistics/standard-deviation/
WEBSep 17, 2020 · The standard deviation is the average amount of variability in your dataset. It tells you, on average, how far each value lies from the mean. A high standard deviation means that values are generally far from the mean, while a low standard deviation indicates that values are clustered close to the mean.
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Calculating standard deviation step by step - Khan Academy
https://www.khanacademy.org/math/statistics-probability/summarizing-quantitative-data/variance-standard-deviation-population/a/calculating-standard-deviation-step-by-step
WEBOverview of how to calculate standard deviation. The formula for standard deviation (SD) is. SD = ∑ | x − μ | 2 N. where ∑ means "sum of", x is a value in the data set, μ is the mean of the data set, and N is the number of data points in the population.
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Standard Deviation Calculator
https://www.calculator.net/standard-deviation-calculator.html
WEBGenerally, calculating standard deviation is valuable any time it is desired to know how far from the mean a typical value from a distribution can be. This free standard deviation calculator computes the standard deviation, variance, …
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Standard Deviation: Interpretations and Calculations - Statistics …
https://statisticsbyjim.com/basics/standard-deviation/
WEBThe standard deviation (SD) is a single number that summarizes the variability in a dataset. It represents the typical distance between each data point and the mean. Smaller values indicate that the data points cluster closer to the mean—the values in the dataset are relatively consistent.
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Standard deviation - Math.net
https://www.math.net/standard-deviation
WEBStandard deviation. Standard deviation is a statistical measure of variability that indicates the average amount that a set of numbers deviates from their mean. The higher the standard deviation, the more spread out the values, while a lower standard deviation indicates that the values tend to be close to the mean.
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Standard Deviation Formulas - Math is Fun
https://www.mathsisfun.com/data/standard-deviation-formulas.html
WEBWork out the Standard Deviation. Step 1. Work out the mean. In the formula above μ (the greek letter "mu") is the mean of all our values ... Example: 9, 2, 5, 4, 12, 7, 8, 11, 9, 3, 7, 4, 12, 5, 4, 10, 9, 6, 9, 4. The mean is: 9+2+5+4+12+7+8+11+9+3+7+4+12+5+4+10+9+6+9+4 20. = 140 20 = 7.
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Standard Deviation and Variance - Math is Fun
https://www.mathsisfun.com/data/standard-deviation.html
WEBA Sample: divide by N-1 when calculating Variance. All other calculations stay the same, including how we calculated the mean. Example: if our 5 dogs are just a sample of a bigger population of dogs, we divide by 4 instead of 5 like this: Sample Variance = 108,520 / 4 = 27,130. Sample Standard Deviation = √27,130 = 165 (to the nearest mm ...
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Population and sample standard deviation review - Khan Academy
https://www.khanacademy.org/math/statistics-probability/summarizing-quantitative-data/variance-standard-deviation-sample/a/population-and-sample-standard-deviation-review
WEBStandard deviation measures the spread of a data distribution. It measures the typical distance between each data point and the mean. The formula we use for standard deviation depends on whether the data is being considered a population of its own, or the data is a sample representing a larger population.
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Standard Deviation - Definition, How to calculate the variance and
https://byjus.com/maths/standard-deviation/
WEBStandard Deviation is a measure which shows how much variation (such as spread, dispersion, spread,) from the mean exists. The standard deviation indicates a “typical” deviation from the mean. It is a popular measure of variability because it returns to the original units of measure of the data set.
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