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EOD – end of data; 0 – numeric type, value is the second number, the following line is one of these keywords: V – valid; NA – not available; ERROR – error; TRUE – true boolean value; FALSE – false boolean value; 1 – string type, the second number is ignored, the following line is the string in double quotes
Excel maintains 15 figures in its numbers, but they are not always accurate; mathematically, the bottom line should be the same as the top line, in 'fp-math' the step '1 + 1/9000' leads to a rounding up as the first bit of the 14 bit tail '10111000110010' of the mantissa falling off the table when adding 1 is a '1', this up-rounding is not undone when subtracting the 1 again, since there is no ...
The false positive rate (FPR) is the proportion of all negatives that still yield positive test outcomes, i.e., the conditional probability of a positive test result given an event that was not present. The false positive rate is equal to the significance level. The specificity of the test is equal to 1 minus the false positive rate.
ParserFunctions allow for the conditional display of table rows, columns or cells (and really, just about anything else). But Parser functions have some limits. But Parser functions have some limits. Basic use
Excel offers many user interface tweaks over the earliest electronic spreadsheets; however, the essence remains the same as in the original spreadsheet software, VisiCalc: the program displays cells organized in rows and columns, and each cell may contain data or a formula, with relative or absolute references to other cells. Excel 2.0 for ...
By Johann M Cherian and Sukriti Gupta (Reuters) -U.S. stock index futures slipped on Friday ahead of a crucial labor market report, at a time when concerns around inflation and the incoming Trump ...
Honey, miso and soy create an umami-rich marinade for rich, meaty salmon. Lighter Side. Lighter Side. People. First-time lottery player wins $5M on scratch-off ticket: 'I didn't think it was real
Data cleansing may also involve harmonization (or normalization) of data, which is the process of bringing together data of "varying file formats, naming conventions, and columns", [2] and transforming it into one cohesive data set; a simple example is the expansion of abbreviations ("st, rd, etc." to "street, road, etcetera").