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In Microsoft Excel, type the followingcode into the cell where you want the Standard Deviation result,using the "unbiased," or "n1" method:
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Salinity Concentration of dissolved salts found in a sample of water
Now, remember how I told you this was way of computingthis? Sometimes, you divide by (n) instead of (n1). It's too complexto explain here. So don't try to go figuring out a standard deviationif you just learned about it on this page. Just be satisfied thatyou've now got a grasp on the basic concept.
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Note: Another quite popular way of calculating volatility (although far less popular than the standard deviation method and used mainly by some volatility traders) is the so called noncentered or zero mean historical volatility. The calculation is very similar to the standard deviation method, but there is a little difference. Both methods are described in the PDF guide of the .
Find out what Cp, Cpk, Cm, Cmk and control limits are.
Standard deviation is the way (historical or realized) volatility is usually calculated in finance. Using the most popular calculation method, historical volatility is the standard deviation of logarithmic returns. Therefore, to some extent, volatility and standard deviation are the same, but…
Agreement between your test result value and the true value; i.e
When we think of image noise in traditional radiographic imaging using screenfilm imaging we are referring to the overall graininess of the image. CT is a type of digital imaging processing in which image noise can be caused by a variety of factors. Noise in CT is mainly related to the following: (1) number of detected photons; (2) matrix size (pixel size); (3) slice thickness; (4) algorithm; (5) electronic noise (detector electronics); (6) scattered radiation; and (7) object size.^{1} Noise limits low contrast resolution and may hide anatomy similar to surrounding tissue. Most pathology imaged in CT is seen in soft tissues such as the lungs, kidney, liver, and brain. To test for image noise a simple cylinder or container of about 20 cm. in diameter is used. The phantom used to calculate the CT number for water and air is used for the noise uniformity test. The phantom is scanned at different slice thicknesses, and gradual increases in mAs. Measure an ROI of about 200300 pixels and find the standard deviation of the CT number at the center of each image. The image field is sampled along the periphery as well as in the center of the image. There should be uniformity in the CT numbers throughout the image. The noise level can be stated as a percentage of image contrast in CT numbers. The stand deviation for noise should be +/ 3. Since CT numbers range from +/1000 HU, noise is less than 0.3%. The maximum standard deviation between the center ROI and any peripheral ROI is less than +/ 5 HU.
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