data analysis for physical scientists featuring excel

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Data Analysis For Physical Scientists

Author : Les Kirkup
ISBN : 9780521883726
Genre : Mathematics
File Size : 69. 46 MB
Format : PDF, ePub
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Introducing data analysis techniques to help undergraduate students develop the tools necessary for studying and working in the physical sciences.

Data Analysis With Excel

Author : Les Kirkup
ISBN : 0521797373
Genre : Science
File Size : 40. 38 MB
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An essential introduction to data analysis techniques using spreadsheets, for undergraduate and graduate students.

Advanced Excel For Scientific Data Analysis

Author : Robert De Levie
ISBN : 0195152751
Genre : Science
File Size : 70. 21 MB
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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 "error" 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.

Statistics For Exercise Science And Health With Microsoft Office Excel

Author : J. P. Verma
ISBN : 9781118855171
Genre : Mathematics
File Size : 84. 63 MB
Format : PDF
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This book introduces the use of statistics to solve a variety of problems in exercise science and health and provides readers with a solid foundation for future research and data analysis. Statistics for Exercise Science and Health with Microsoft Office Excel: Aids readers in analyzing their own data using the presented statistical techniques combined with Excel Features comprehensive coverage of hypothesis testing and regression models to facilitate modeling in sports science Utilizes Excel to enhance reader competency in data analysis and experimental designs Includes coverage of both binomial and poison distributions with applications in exercise science and health Provides solved examples and plentiful practice exercises throughout in addition to case studies to illustrate the discussed analytical techniques Contains all needed definitions and formulas to aid readers in understanding different statistical concepts and developing the needed skills to solve research problems

Python For Data Analysis

Author : Wes McKinney
ISBN : 9781449319793
Genre : Computers
File Size : 45. 7 MB
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Presents case studies and instructions on how to solve data analysis problems using Python.


Author : Mikhail I. Katsnelson
ISBN : 9780521195409
Genre : Science
File Size : 49. 73 MB
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An important introduction to graphene, its physics and potentially significant applications, for graduate students, physicists and materials science researchers.

Compositional Data Analysis

Author : Vera Pawlowsky-Glahn
ISBN : 9781119977612
Genre : Mathematics
File Size : 68. 13 MB
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It is difficult to imagine that the statistical analysis of compositional data has been a major issue of concern for more than 100 years. It is even more difficult to realize that so many statisticians and users of statistics are unaware of the particular problems affecting compositional data, as well as their solutions. The issue of ``spurious correlation'', as the situation was phrased by Karl Pearson back in 1897, affects all data that measures parts of some whole, such as percentages, proportions, ppm and ppb. Such measurements are present in all fields of science, ranging from geology, biology, environmental sciences, forensic sciences, medicine and hydrology. This book presents the history and development of compositional data analysis along with Aitchison's log-ratio approach. Compositional Data Analysis describes the state of the art both in theoretical fields as well as applications in the different fields of science. Key Features: Reflects the state-of-the-art in compositional data analysis. Gives an overview of the historical development of compositional data analysis, as well as basic concepts and procedures. Looks at advances in algebra and calculus on the simplex. Presents applications in different fields of science, including, genomics, ecology, biology, geochemistry, planetology, chemistry and economics. Explores connections to correspondence analysis and the Dirichlet distribution. Presents a summary of three available software packages for compositional data analysis. Supported by an accompanying website featuring R code. Applied scientists working on compositional data analysis in any field of science, both in academia and professionals will benefit from this book, along with graduate students in any field of science working with compositional data.

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