
Statistical Inference by George Casella
Basics of probability to theory of statistical inference using techniques, definitions, concepts that are statistical, natural extensions, consequences, of previous concepts. Topics from a standard inference course: distributions, random variables, data reduction, point estimation, hypothesis testing, interval estimation, regression.-
Practical Statistics for Medical Research
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Bayesian Data Analysis
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Statistical Rethinking
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Introduction to Multivariate Analysis
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Introduction to Probability, Second Edition
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Statistics for Epidemiology
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Statistics for Technology
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Modelling Survival Data in Medical Research
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The Analysis of Time Series
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Problem Solving
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An Introduction to Generalized Linear Models, First Edition
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Epidemiology
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The BUGS Book
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Applied Stochastic Modelling
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Modern Data Science with R
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Statistics in Research and Development
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Modelling Survival Data in Medical Research, Second Edition
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An Introduction to Generalized Linear Models
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Applied Non-Parametric Statistical Methods, Second Edition
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Surrogates
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Statistics in Engineering
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Elements of Simulation
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Computer-Aided Multivariate Analysis, Fourth Edition
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Applied Nonparametric Statistical Methods, Third Edition
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Statistics in Human Genetics and Molecular Biology
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Pragmatics of Uncertainty
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Markov Chain Monte Carlo
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Nonparametric Inference
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Foundations of Bayesian Statistics for Data Scientists
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Time Series
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Introduction to Modern Randomization-Based Design and Analysis for Causal Inference
Professor George Casella completed his undergraduate education at Fordham University and graduate education at Purdue University. He served on the faculty of Rutgers University, Cornell University, and the University of Florida. His contributions focused on the area of statistics including Monte Carlo methods, model selection, and genomic analysis. He was particularly active in Bayesian and empirical Bayes methods, with works connecting with the Stein phenomenon, on assessing and accelerating the convergence of Markov chain Monte Carlo methods, as in his Rao-Blackwellisation technique, and recasting lasso as Bayesian posterior mode estimation with independent Laplace priors.
Casella was named as a Fellow of the American Statistical Association and the Institute of Mathematical Statistics in 1988, and he was made an Elected Fellow of the International Statistical Institute in 1989. In 2009, he was made a Foreign Member of the Spanish Royal Academy of Sciences.
After receiving his doctorate in statistics from Purdue University, Professor Roger Berger held academic positions at Florida State University and North Carolina State University. He also spent two years with the National Science Foundation before coming to Arizona State University in 2004. Berger is co-author of the textbook "Statistical Inference," now in its second edition. This book has been translated into Chinese and Portuguese. His articles have appeared in publications including Journal of the American Statistical Association, Statistical Science, Biometrics and Statistical Methods in Medical Research. Berger's areas of expertise include hypothesis testing, (bio)equivalence, generalized linear models, biostatistics, and statistics education.
Berger was named as a Fellow of the American Statistical Association and the Institute of Mathematical Statistics.
| SKU | Unavailable |
| ISBN 13 | 9781032593036 |
| ISBN 10 | 1032593032 |
| Title | Statistical Inference |
| Author | George Casella |
| Series | Chapman And Hall Crc Texts In Statistical Science |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Taylor & Francis Ltd |
| Year published | 2024-05-23 |
| Number of pages | 535 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |































