A01=Robert Lupton
Accuracy and precision
Analysis of variance
Asymptotic distribution
Asymptotic theory
Author_Robert Lupton
Bayes' theorem
Bayesian
Bayesian statistics
Bias of an estimator
Binomial distribution
Bootstrapping (statistics)
Calculation
Category=PBT
Cauchy distribution
Central limit theorem
Characteristic function (probability theory)
Confidence interval
Convolution theorem
Correlation coefficient
Covariance matrix
Cumulative distribution function
Degeneracy (mathematics)
Degrees of freedom (statistics)
Distribution function
Efficiency (statistics)
Einstein notation
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Estimation
Estimator
Expectation value (quantum mechanics)
F-test
Function (mathematics)
Gauss-Markov theorem
Identity matrix
Independence (probability theory)
Likelihood function
Likelihood-ratio test
Linear regression
Mann-Whitney U test
Mathematical statistics
Maximum likelihood estimation
Moment (mathematics)
Monte Carlo method
Multivariate normal distribution
Neyman-Pearson lemma
Nonparametric statistics
Normal distribution
Order statistic
Parameter
Pearson product-moment correlation coefficient
Poisson point process
Probability
Probability density function
Probability distribution
Ratio test
Resampling (statistics)
Sample mean and covariance
Sampling (statistics)
Scientific notation
Score test
Standard deviation
Statistic
Statistical hypothesis testing
Statistician
Statistics
Student's t-test
Test statistic
Theory
Uniform distribution (discrete)
Variable (mathematics)
Variance
Variance-stabilizing transformation
Wilcoxon signed-rank test
Product details
- ISBN 9780691074290
- Weight: 454g
- Dimensions: 152 x 235mm
- Publication Date: 01 Aug 1993
- Publisher: Princeton University Press
- Publication City/Country: US
- Product Form: Hardback
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Aimed at a diverse scientific audience, including physicists, astronomers, chemists, geologists, and economists, this book explains the theory underlying the classical statistical methods. Its level is between introductory "how to" texts and intimidating mathematical monographs. A reader without previous exposure to statistics will finish the book with a sound working knowledge of statistical methods, while a reader already familiar with the standard tests will come away with an understanding of their strengths, weaknesses, and domains of applicability. The mathematical level is that of an advanced undergraduate; for example, matrices and Fourier analysis are used where appropriate. Among the topics covered are common probability distributions; sampling and the distribution of sampling statistics; confidence intervals, hypothesis testing, and the theory of tests; estimation (including maximum likelihood); goodness of fit (including c2 and Kolmogorov-Smirnov tests); and non-parametric and rank tests. There are nearly one hundred problems (with answers) designed to bring out points in the text and to cover topics slightly outside the main line of development.
Robert Lupton is a member of the professional staff in astrophysical sciences at Princeton University.
