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English sentences with data deviation in context,

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After a few weeks of collecting data, I played around with the factor until the deviation of different runs that “felt the same” was as low as possible.
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One could probably take the full data available now and calculate a factor which, based on the weekly average RFI, shows the smallest standard deviation.
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It quantifies the relationship between the the standard deviation (basically the distance your data is to itself...how spread out it is) to the mean (the average).
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In other words, while the standard deviation tells you how far you have to go for the data to be statistically different the relative standard deviation tells you what percent of the average that is.
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I compare this data to the covariance and standard deviation of each players actual points they have scored throughout the year (mostly use last years data for the first 4 or 5 weeks then I start to use current years stats).
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My rough ballpark (going off of data that has a large standard deviation and thus isn't that indicative of a average) is a decrease of 27 points, putting PFM at 285 points next year.
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The bulk of the posts (the automated ones) are essentially random data (doesnt mean it cant be decrypted), the way we can tell that is from the standard deviation which basically tells you how random the data is.
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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.
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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.
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The means all fall within one standard deviation of each other, so I think it would be hard to argue that they differ, but maybe the data are distributed bimodally such that the means do not capture the signal that you are looking for.
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In this particular case the means may fall within one standard deviation, but I have 40 data sets on hand.
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Think we'd have to calculate the Standard deviation for this and I'm no mathemagician to work it out with the data we have at the moment.
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Deviation data is harder to come by, but a cursory search indicates that 90% are below 200lbs.
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Results of four consecutive tests yielded an average data use of 39MB/hour for the target device, with a deviation of less than 2 MB.
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In terms of physics, there have been some experimental tests of gravity working through "large" extra dimensions, including very precise measurements of gravitational forces at small distances (down to ~100 microns) to see if there are deviations from Newtons laws, and looking at data from the Large Hadron Collider to see if there are deviations from the Standard Model consistent with large extra dimensions (e.g.
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We've only been working on Dutch spatial data, which is almost always projected in double stereographic with pretty much no deviation from the standard line at any place in the Netherlands (a few meters max around the edges, IIRC).
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The standard deviation has the same dimension as the data, and hence is comparable to deviations from the mean.
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Categorically from a data point of view though, wouldn't you want to look at the 50th percentile because by definition we'll encompass most of the population in the nearest standard deviations?
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if i remember right from what someone posted long long ago, about 500 data points would equal about 5% deviation.
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A chi-square would rely on the standard deviation being known, not estimated (or based on so much data you'd be happy to say that its estimate had converged to the population value).
source: Reddit

If you can assume your data come from a population that is symmetric, you can use similar theory to confidence intervals and state something is a potential outlier if it lies 3 standard deviations from the mean.
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I took the mean over the set of data from market sold prices and calculated for both standard deviations and averaged both.
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For example, I could get the standard deviation, max, min, and mean for a data set...
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Were you given those mean values and standard deviations or did you calculate them based on given data?
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Saying that on day 363, global ice extend in 2014 is higher than average says almost nothing at all - it is a remarkably average year based on this data almost always staying within one standard deviation of the mean in this data.
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If I am not mistaken, that is not the standard deviation, because in your picture, it would be only a point of the data set, while the standard deviation is a statistical characteristic of a set, which is defined even for a set of equal points.
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Because all data fits a perfect bell curve with extremes several standard deviations from the norm.
source: Reddit

If you want to look at historical data there's actually very little change over time, so the standard deviation will be quite low.
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Standard deviation over the entire population, is completely unrelated to the standard deviation over non-random subset of the data.
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In a normal distribution, 50% of data lie within 2/3 standard deviations of the mean, and the 2" difference from 5'10" to 6' happens to be 2/3 of the 3" standard deviation.
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One standard deviation above and below the mean encompasses about 68% of the data, confirming /u/FedoraToppedLurker's estimation that 16% of men are shorter than 5'7".
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The wages of CEOs are probably not figured in because they are so wildly disproportionate to the rest of the data points that they would cause huge deviations in the overall curve.
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Any deviation may result in data loss, file corruption, permissions issues, and other bad things.
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Any deviation from the expectation, no matter the magnitude, is statistically significant if the uncertainty is on the same scale as the data.
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The current data suggests he's within one standard deviation of the average.
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Given that they haven't eaten for so many hours, it would be quite telling if your data indicated a deviation (large gap in fares before sunup and after sundown) where the cabbie is eating.
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i keep a data warehouse of the info sorted by type (type of dev) and hours used versus hours estimated, and the deviation.
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Either their answers conform with your data and no correction is necessary, or their answers are a significant deviation and they are corrected.
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A data set's standard deviation is the average distance a data point is from the mean.
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If I used "moving standard deviation" I couldn't even plot the line together with the data points.
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my only gripe would be you may need to look at more definite data for standard deviations based on average times to find an appropriate scaling for each tier
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Between updates, the spacecraft can use data from star trackers, gyroscopes, and accelerometers to keep track of deviations in their path.
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As someone who works on these types of migrations and data centers regularly, you'd be surprised at what can severely delay your server infrastructure getting into place at the desired time.
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You can argue how great Python is for parsing terrible data formats.
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Like all theories, it's open to new data.
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Low bandwith can throttle data and make the ping higher.
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Theorists try to get their work experimentally tested by experimentalists, and experimentalists give theorists experimental data which theorists use to build theories/models.
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I did a whole range of heights and speeds by taking data of the highest and fastest carousels and punching the equation and data into an excel spreadsheet and then making awesome graphs of the data to explain the trends.
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I use torque and a odb2 sensor for ecu data.
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I was on mobile so unable to type out a long discussion on this, but that's precisely one of the objections to the data I was going to raise.
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