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You should generally select a data type for a column that has the smallest possible length and a legitimate range of values for all the values that a column can hold.

Written this way, one of these declarations will appear in the cells for each salesperson, once it s copied for all. I think they d prefer the $250, but be that as it may, note that textual if true/false consequences require quotes around them. And nothing stops you from incorporating other functions into IF, as long as you remember to keep your parentheses in line. Let s get back to Alice, and her 83 test average: =IF(AVERAGE(D10:H10)>85, Honor Roll , Nice Try ) If Alice s average were to exceed 85, Honor Roll appears in whatever cell the statement is written. In this case we see that AVERAGE is used here to establish the logical test and once you ve become practiced with nesting functions inside other ones, such as the example we re studying here, you can really start to rock n roll. The data possibilities multiply exponentially. There s one more function we can squeeze into into this sampler, and this one has real-world pertinence PMT short for Payment a financial formula that can easily tell you how much money you can expect to pay for a mortgage like it or not. Stripped to its essentials, PMT has three arguments: =PMT(rate,nper,pv) Rate stands for your annual rate, one that will need to be divided by 12, or whatever the payment interval (example coming shortly). Nper signifies the number of payments you need to make across the life of the mortgage, and Pv denotes the present value of the mortgage. Here s that example: you want to take out a 30-year, $200,000 mortgage at an interest rate of 5.2%. Let s enter these three values in cells B12, C12, and D12, shown in Figure 3 41: (Again, we haven t formatted these values.)

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Number data types can represent values either precisely or approximately. Several data types for storing numbers support the storage of integer quantities, such as 1, 2, or 100. Other values, such as 1 divided by 3, cannot be represented precisely. To accommodate values that cannot be represented precisely or whose length would be prohibitive to represent precisely, SQL Server offers approximate data types. In many cases, data types for precise numbers represent integer values with a scale of zero (no digits to the right of the decimal point). Some data types for numbers represent values precisely even while they permit the inclusion of digits to the right of the decimal point. Three data types like this are money, smallmoney, and decimal (or numeric).

SQL Server offers two data types for representing date and time values, datetime and smalldatetime. These data types store their values as numbers with digits to the left and right of a decimal point. Digits to the left of the decimal point represent whole days. Digits to the right of the decimal point denote fractions of a day. The datetime and smalldatetime data types have different lengths, which enable these two data types to represent a different range of date and time values to different levels of accuracy. datetime and smalldatetime have characteristics that closely resemble the characteristics for numbers. For example, number data types and data types for dates and times have fixed lengths. In addition, both sets of data types have a legitimate range of values (from a minimum number or beginning date and time to a maximum number or ending date and time). The accuracy of date and time data types (1 minute for smalldatetime vs. 3.33 milliseconds for datetime) corresponds roughly to scale.

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