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This kind of data error, if not detected and eliminated, can skew the results produced by almost any mechanical trading model Although anything but innocuous, such errors are obvious, are easy to detect (even automatically), and are readily corrected or otherwise handled More innocuous, albeit less obvious and harder to find, are the common, small errors in the settling price, and other numbers reported by the exchanges, that are frequently passed on to the consumer by the data vendor Better data vendors repeatedly check their data and post corrections as such errors are detected For example, on an almost daily basis, Pinnacle Data posts error corrections that are handled automatically by its software Many of these common, small errors are not seriously damaging to software-based trading simulations, but one never knows for sure.

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C# Code 128 Reader SDK to read, scan Code 128 in C#.NET class ...
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There have been many database marketing failures during the past two decades, from which companies have learned what does not work. A few of the reasons are Failure to test a strategy on a small sample before a rollout. Database marketing is particularly adapted to setting up tests, which can prove the validity of any idea before serious money is spent on it. Database marketers know this. Company management usually does not. Pushing for quick pro ts has led many companies to fail with ideas that could easily have been tested on a small scale rst. Failure to set aside control groups. If you are going to spend a million dollars on a group of customer communications designed to boost retention or sales, you always should set aside a group that does not

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The American Cancer Society has information and tips on quitting smoking. For information call 1-800-ACS-2345 or visit www.cancer.org. You may also contact the American Heart Association at 1-800-242-1793 or at www.amhrt.org; the American Lung Association at 1-800-586-4872 or at www.lungusa.org; or the National Cancer Institute at 1-800-4-CANCER or at www.nci.nih.gov.

Depending on the sensitivity of the trading or forecasting model being analyzed, and on such other factors as the availability of data-checking software, it may be worthwhile to run miscellaneous statistical scans to highlight suspicious data points There are many ways to flag these data points, or ourlieru, as they are sometimes referred to by statisticians Missing, extra, and logically inconsistent data points are also occasionally seen; they should be noted and corrected As an example of data checking, two data sets were run through a utility program that scans for missing data points, outliers, and logical inconsistencies The results appear in Tables I-1 and 1-2, respectively Table I 1 shows the output produced by the data-checking program when it was used on Pinnacle Data Corporation s (800-724-4903) end-of-day, continuous-contract data for the S&P 500 futures.

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get the communications in order to prove the value of the effort Many companies still fail to do this The result, of course, can be disaster If the economy is going down and your sales are going down, you may assume that your methods are not working If you set aside a control group, however, you might nd that the sales of your test group went down less than those of the control group, proving that your communication program worked, even in adverse circumstances Failure to develop strategies that work Database marketing has often worked so well that some people have thought that it was the database and the software that were producing the miracles It wasn t What produced the miracles were strategies that resonated with the particular audiences represented in the databases.

The utility found no illogical prices or volumes in this data set; there were no observed instances of a high that wan less than the close, a low that was greater than the open, a volume that was less than zero, or of any cognate data faux pas Rvo data points (bars) with suspiciously high ranges, however, were noted by the software: One bar with unusual range occurred on 1 O/l 9/87 (or 871019 in the report) The other was dated 10/13/89 The abnormal range observed on 10/19/87 does not reflect an error, just tbe normal volatility associated with a major crash like that of Black Monday; nor is a data error responsible for the aberrant range seen on 10/13/89, which appeared due to the so-called anniversary effect Since these statistically aberrant data points were not errors, corrections were unnecessary..

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code 128 can be generated in many kinds of platforms,just take this guide for code 128 in asp.net for example. besides,as for barcode reader ...
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