Data Analysis for Scientists and Engineers (eBook)

Edward L. Robinson (Autor)

eBook Download: PDF

2016
408 Seiten
Princeton University Press (Verlag)
978-1-4008-8306-6 (ISBN)

Infos

Data Analysis for Scientists and Engineers is a modern, graduate-level text on data analysis techniques for physical science and engineering students as well as working scientists and engineers. Edward Robinson emphasizes the principles behind various techniques so that practitioners can adapt them to their own problems, or develop new techniques when necessary.Robinson divides the book into three sections. The first section covers basic concepts in probability and includes a chapter on Monte Carlo methods with an extended discussion of Markov chain Monte Carlo sampling. The second section introduces statistics and then develops tools for fitting models to data, comparing and contrasting techniques from both frequentist and Bayesian perspectives. The final section is devoted to methods for analyzing sequences of data, such as correlation functions, periodograms, and image reconstruction. While it goes beyond elementary statistics, the text is self-contained and accessible to readers from a wide variety of backgrounds. Specialized mathematical topics are included in an appendix.Based on a graduate course on data analysis that the author has taught for many years, and couched in the looser, workaday language of scientists and engineers who wrestle directly with data, this book is ideal for courses on data analysis and a valuable resource for students, instructors, and practitioners in the physical sciences and engineering.In-depth discussion of data analysis for scientists and engineersCoverage of both frequentist and Bayesian approaches to data analysisExtensive look at analysis techniques for time-series data and imagesDetailed exploration of linear and nonlinear modeling of dataEmphasis on error analysisInstructor's manual (available only to professors)

Autor

Edward L. Robinson is the William B. Blakemore II Regents Professor of Astronomy at the University of Texas, Austin.

Produkt-Details

• Zusatzinfo: 96 line illus. 7 tables.
• Verlagsort: Princeton
• Sprache: englisch
• Themenwelt: Informatik ► Datenbanken ► Data Warehouse / Data Mining
• Themenwelt: Mathematik / Informatik ► Mathematik
• Themenwelt: Naturwissenschaften ► Physik / Astronomie
• Themenwelt: Technik
• Schlagworte: Accuracy and precision • Amplitude • autocorrelation • autocovariance • Autoregressive model • Basis (linear algebra) • Bayesian • Bayesian inference • Bayesian Statistics • Bayes' Theorem • Bias of an estimator • Calculation • central limit theorem • Characterization (mathematics) • Confidence interval • Confidence region • conjugate prior • convolution • Convolution Theorem • Correlation and dependence • Covariance function • Covariance matrix • Credible interval • Cross-covariance • Cumulative distribution function • Determinant • Diagram (category theory) • differential equation • Dirac delta function • dot product • Eigenvalues and Eigenvectors • Equation • Error analysis (Mathematics) • estimation • Estimation theory • exponential function • Fixed point (mathematics) • Forcing function (differential equations) • fourier analysis • Fourier series • Fourier transform • frequentist inference • Function (mathematics) • gaussian noise • Gibbs Sampling • Harmonic oscillator • Identity matrix • Joint probability distribution • Least Squares • Likelihood Function • Likelihood-ratio test • linear differential equation • Linearization • Linear least squares (mathematics) • Markov Chain • Markov Chain Monte Carlo • Maxima and minima • maximum likelihood estimation • Measurement • Metropolis–Hastings algorithm • Moment (mathematics) • Monte Carlo Method • Newton's method • Normal distribution • Numerical Integration • Parameter • Parity (mathematics) • Parseval's theorem • Permutation • Poisson distribution • Polynomial Regression • posterior probability • Principal Component Analysis • Prior probability • Probability • Probability Distribution • Probability Distribution Function • Proportionality (mathematics) • Pseudorandom number generator • quadratic function • Quantity • Random Number • Rate of Convergence • Scalar (physics) • Simplex Algorithm • Simultaneous Equations • Sinc function • Sine Wave • Spectral density • standard deviation • Statistic • Statistical hypothesis testing • Statistical Mechanics • Stochastic process • Summation • The Signal and the Noise • transformation matrix • Trigonometric Functions • Variable (mathematics) • Variance
• ISBN-10: 1-4008-8306-7 / 1400883067
• ISBN-13: 978-1-4008-8306-6 / 9781400883066