274 Part I EXAM PREPARATION the group. The
274 Part I EXAM PREPARATION the group. The STDDEV() and STDDEVP() functions calculate the standard deviation of the group. Variance and standard deviation are used in statistics to determine the spread of a sample set. A sample set has a high variance and a high standard deviation if there is a wide range of values in the sample set. If there is a small range of values, then the variance and standard deviation is smaller. The STDEVP() and STDEV() functions differ in that the STDEV() determines the sample standard deviation, while STDEVP() returns the population standard deviation. VAR() and VARP() are similar. See the Suggested Reading section at the end of the chapter if you really want more information. Data Management Aggregate Functions Four functions specifically pertain to helping you manage data. Three of them revolve around checksums. A checksum is a number generated from a data value that essentially summarizes the data value. For example, if you have the string This is a test , the checksum is 575031869. That doesn t mean much, but if you store that value, and then change the string to The test is over , which has a checksum of 270787094, you can quickly tell by comparing the checksums that the value of the string changed. If you re working with large data sets, though, the ability to compare checksums saves an immense amount of time over comparing strings together. The computer science folks call this a hash function. Basically, it s a way to compress your data for comparison purposes to make it easier to compare. There is a small chance that two pieces of data will have the same checksum. How small? Well, 2 in 4 billion. The checksums return some number that s an integer, and the chances that two pseudorandom integers will be the same are very small. So this is actually a very useful function for detecting changes in rows. The CHECKSUM() and CHECKSUM_BINARY() functions aren t true aggregate functions. They return a checksum for whatever you ask them to typically for a row. The difference between CHECKSUM() and CHECKSUM_BINARY() is that a CHECKSUM() checks data that s been localized for the server, whereas CHECKSUM_BINARY() checks raw data. In this case, localized means that the string is translated to how it would compare prior to computing the checksum. So, if you re on a server that s set up as not case sensitive, which is the default, the
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