Excel is by far the most widely distributed data analysis software but few users are aware of its full powers. Advanced Excel For Scientific Data Analysis takes off from where most books dealing with scientific applications of Excel end. It focuses on three areas-least squares, Fourier transformation, and digital simulation-and illustrates these with extensive examples, often taken from the literature. It also includes and describes a number of sample macros and functions to facilitate common data analysis tasks. These macros and functions are provided in uncompiled, computer-readable, easily modifiable form; readers can therefore use them as starting points for making their own personalized data analysis tools. Detailed descriptions and sample applications of standard and specialized uses of least squares for fitting data to a variety of functions, including resolving multi-component spectra; standard processes such as calibration curves and extrapolation; custom macros for general qerrorq propagation, standard deviations of Solver results, weighted or equidistant least squares, Gram-Schmidt orthogonalization, Fourier transformation, convolution and deconvolution, time-frequency analysis, and data mapping. There are also worked examples showing how to use centering, the covariance matrix, imprecision contours, and Wiener filtering and custom functions for bisections, Lagrange interpolation, Euler and Runge-Kutta integration.Excel is by far the most widely distributed data analysis software but few users are aware of its full powers. Advanced Excel For Scientific Data Analysis takes off from where most books dealing with scientific applications of Excel end.

Title | : | Advanced Excel for Scientific Data Analysis |

Author | : | Robert De Levie |

Publisher | : | Oxford University Press, USA - 2004 |

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