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- W4383750571 abstract "In this chapter we consider a problem we have examined earlier, which is how to derive information from data. This was central to Chapter 5 , when we derived interpolation formulas, and also in Chapter 8 , where we investigated ways to use linear and nonlinear regression. In this chapter, three different situations are considered. The first two are examples illustrating the usefulness of the singular value decomposition (SVD) in data analysis. The SVD is explained in Section 4.6 . All three methods make use of the regression material covered in Section 8.3 . The goal is to have a method that can be used to find connections between experimentally determined quantities, even though there is no obvious reason why they have to be connected. It is easiest to explain this using an example. In addition to introducing how the SVD can be used to find the connections, it will also show how the method overlaps with the regression material considered in Chapter 8 ." @default.
- W4383750571 created "2023-07-11" @default.
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- W4383750571 date "2023-01-01" @default.
- W4383750571 modified "2023-09-27" @default.
- W4383750571 title "Data Analysis" @default.
- W4383750571 doi "https://doi.org/10.1007/978-3-031-22430-0_10" @default.
- W4383750571 hasPublicationYear "2023" @default.
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