Statistics books by astronomers and
Some older volumes of interest include:
Logical Data Analysis for the Physical Sciences
by P. C. Gregory (2005). After introduction to probabilities,
and frequentist inference, this monograph presents Bayesian
applications to data with Gaussian and Poisson errors, linear and
nonlinear modelling, maximum entropy, Markov chain Monte Carlo
integration, and spectral analysis of time series. Provides worked
examples with astronomical data, problem sets, and codes associated
Data Analysis for Astrophysics
by Fionn Murtagh (c. 2005).
Unpublished lecture notes for a graduate course for astronomers with
astronomical applications emphasizing clustering (hierarchical, minimal
spanning tree, Voronoi tesselation, partitioning,
mixture models, self-organizing maps, ultrametric spaces, P-adic
and discriminant analysis (Bayes and nonparametric discrimination,
perceptron). An update of his 1987 monograph appears here.
Techniques for Signal Processing
by Abdelhak M. Zoubir and
D. Robert Iskander (2004).
This book serves as a handbook on `bootstrap' for engineers, to analyze
complicated data with little or no model assumptions. Bootstrap has
found many applications in engineering field including, artificial
neural networks, biomedical engineering, environmental engineering,
image processing, and Radar and sonar signal processing.
Majority of the applications are taken from signal processing
Statistics for Astronomers
by Jasper V. Wall & C. R. Jenkins (2003). Textbook on
methods relevant for observational astronomy with emphasis on Bayesian
approaches and worked problems. Covers probability, correlation,
hypothesis testing, Bayesian models, time series analysis, luminosity
functions and clustering.
Reduction and Error Analysis for the Physical Sciences
by Philip Bevington & D. Keith Robinson (2003, 2nd
ed.). Popular text with code covering error analysis, Monte Carlo
techniques, least-squares fitting, maximum-likelihood, and
Image and Data Analysis
by Jean-Luc Starck and Fionn Murtagh (2002). Advanced
techniques for treating astronomical data including data filtering
& storage, image processing (edge detection, segmentation, pattern
recognition), image compression, source detectcion, multiscale analysis
using wavelet transforms, deconvolution, multivariate data, entropies,
catalogs and Virtual Observatories.
of the Galaxy Distribution
by Vicent J. Martinez and Enn Saar (2002). Comprehensive
monograph on the large-scale galaxy of the universe traced by galaxy
redshift surveys. It reviews the astronomical observations,
statistical techniques and cosmological inferences.
of Data Analysis
by Prasenjit Saha. Brief introductory book covering
Gaussian & Poisson distributions, Monte Carlo methods, least
squares, nonlinear regression, and entropy. Available free on the
and Statistics in Experimental Physics
by Byron P. Roe (2001, 2nd edition) Textbook covering
comcepts, statistical distributions, Monte Carlo methods, central limit
theorem, correlation coefficients, curve fitting with constraints
andconfidence belts, likelihood ratios, least-squares and robust
errors in x and y), Poisson problems. Problem sets with
Analysis: Statistical and Computational Methods for Scientists and
by Siegmund Brandt (1999, 3rd edition). Volume
bridging the gap between physical experiment and statistical
theory. Includes Monte Carlo, maximum likelihood and least
squares methods; hypothesis tests, analysis of variance, polynomial
regression, and time series analysis. Code on CD-ROM.
by Glen Cowan (1998). Guide to practical applications of
statistics in expermental physical science with examples from particle
physics. Includes Monte Carlo methods; parameter estimation
(maximum likelihood, least squares, moments); errors, limits and
confidence intervals; and characteristic functions.
processing and Data Analysis: The Multiscale Approach
by J.-L. Starck, F. Murtagh & A. Bijaoui (1998).
Technical monograph on the use of wavelets for multiscale analysis of
astronomical, engineering, remote sensing, and medical images.
by G. Jogesh Babu & Eric D. Feigelson (1996). A review
of research topics on the methodology of astronomical data analysis
including resampling methods, spatial point processes, symmetrical
linear regressions, multivariate classification, time series analysis,
censoring and truncation. Introduces astronomical problems to
A Bayesian Tutorial
by Devinder Sivia (1996). A clear introduction by a
physicist covering parameter estimation, model selection, assigning
probabilities, nonparametric estimation, and experimental design.
A Guide to the Use of Statistical Methods in the Physical Sciences
by Roger J. Barlow (1993). Introductory treatment of
parameter estimation (least squares, maximum likelihood), hypothesis
Bayesian statistics and non-parametric methods.
in Theory and Practice
by Robert Lupton (1993). Intermediate-level monograph aimed
at physical scientists explaining probability distributions, sampling
statistics, confidence intervale, hypothesis testing, maximum
likelihood estimation, goodness-of-fit, and nonparametric rank
tests. Includes problems with answers.
Practical Guide to Data Analysis for Physical Science Students
by Louis Lyons (1991). Undergraduate text for
interpretation of experiments including distributions and moments,
Gaussian errors, combining results, least-squares fitting, weighting
and confidence intervals, parameter testing.
nuclear and particle physicists (Louis Lyons, 1986)
E. T. Jaynes:
Papers on probability, statistics and statistical physics (E. T.
Analysis (Fionn Murtagh, 1987)
The History of
Statistics: The Measurement of Uncertainty Before 1900 (Stephen
M. Stigler, 1986)
Methods in Experimental Physics (W. A. Eadie et al., 1971)
Method of least
squares and principles of the theory of observations (I. V.
Observations (William M. Smart, 1958)
Astronomy (Robert J. Trumpler & Harold F. Weaver, 1953)
Physical Statistics (Robert
B. Lindsay, 1941)
Inference (Harold Jeffreys, 1937)
On the algebraical
and numerical theory of errors of observations and the combination of
observations (George B.
combination of observations least subject to error (Carl F.
1823, English ed 1995)
to CASt bibliographies