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Functions that have more than one result may be implemented with lookup tables that are arrays of structures. As mentioned, there are intermediate solutions that use tables in combination with a small amount of computation, often using interpolation. Pre-calculation combined with interpolation can produce higher accuracy for values that fall ...
In the figure, the fraction 1/9000 is displayed in Excel. Although this number has a decimal representation that is an infinite string of ones, Excel displays only the leading 15 figures. In the second line, the number one is added to the fraction, and again Excel displays only 15 figures. In the third line, one is subtracted from the sum using ...
Column labels are used to apply a filter to one or more columns that have to be shown in the pivot table. For instance if the "Salesperson" field is dragged to this area, then the table constructed will have values from the column "Sales Person", i.e., one will have a number of columns equal to the number of "Salesperson". There will also be ...
Covering indexes are each for a specific table. Queries which JOIN/ access across multiple tables, may potentially consider covering indexes on more than one of these tables. [7] A covering index can dramatically speed up data retrieval but may itself be large due to the additional keys, which slow down data insertion and update.
A spreadsheet is essentially just one table, whereas a database is a collection of many tables with machine-readable semantic relationships. While it is true that a workbook that contains three sheets is indeed a file containing multiple tables that can interact with each other, it lacks the relational structure of a database.
Slice is the act of picking a rectangular subset of a cube by choosing a single value for one of its dimensions, creating a new cube with one fewer dimension. [5] The picture shows a slicing operation: The sales figures of all sales regions and all product categories of the company in the year 2005 and 2006 are "sliced" out of the data cube.
OLAP tools enable users to analyse multidimensional data interactively from multiple perspectives. OLAP consists of three basic analytical operations: consolidation (roll-up), drill-down, and slicing and dicing. [6]: 402–403 Consolidation involves the aggregation of data that can be accumulated and computed in one or more dimensions. For ...
The problem of multiple comparisons received increased attention in the 1950s with the work of statisticians such as Tukey and Scheffé. Over the ensuing decades, many procedures were developed to address the problem. In 1996, the first international conference on multiple comparison procedures took place in Tel Aviv. [3]