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Books in Statistics and probability

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21-30 of 233 results in All results

Basic Statistics with R

  • 1st Edition
  • February 20, 2021
  • Stephen C. Loftus
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 2 0 7 8 8 - 8
  • eBook
    9 7 8 - 0 - 1 2 - 8 2 0 9 2 6 - 4
Basic Statistics with R: Reaching Decisions with Data provides an understanding of the processes at work in using data for results. Sections cover data collection and discuss exploratory analyses, including visual graphs, numerical summaries, and relationships between variables - basic probability, and statistical inference - including hypothesis testing and confidence intervals. All topics are taught using real-data drawn from various fields, including economics, biology, political science and sports. Using this wide variety of motivating examples allows students to directly connect and make statistics essential to their field of interest, rather than seeing it as a separate and ancillary knowledge area. In addition to introducing students to statistical topics using real data, the book provides a gentle introduction to coding, having the students use the statistical language and software R. Students learn to load data, calculate summary statistics, create graphs and do statistical inference using R with either Windows or Macintosh machines.

Data Science: Theory and Applications

  • 1st Edition
  • Volume 44
  • February 12, 2021
  • C.R. Rao + 1 more
  • English
  • Hardback
    9 7 8 - 0 - 3 2 3 - 8 5 2 0 0 - 5
  • eBook
    9 7 8 - 0 - 3 2 3 - 8 5 2 0 1 - 2
Data Science: Theory and Applications, Volume 44 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of interesting topics, including Modeling extreme climatic events using the generalized extreme value distribution, Bayesian Methods in Data Science, Mathematical Modeling in Health Economic Evaluations, Data Science in Cancer Genomics, Blockchain Technology: Theory and Practice, Statistical outline of animal home ranges, an application of set estimation, Application of Data Handling Techniques to Predict Pavement Performance, Analysis of individual treatment effects for enhanced inferences in medicine, and more. Additional sections cover Nonparametric Data Science: Testing Hypotheses in Large Complex Data, From Urban Mobility Problems to Data Science Solutions, and Data Structures and Artificial Intelligence Methods.

Introduction to Probability and Statistics for Engineers and Scientists

  • 6th Edition
  • September 11, 2020
  • Sheldon M. Ross
  • English
  • Hardback
    9 7 8 - 0 - 1 2 - 8 2 4 3 4 6 - 6
  • eBook
    9 7 8 - 0 - 1 2 - 8 1 7 7 4 7 - 1
Introduction to Probability and Statistics for Engineers and Scientists, Sixth Edition, uniquely emphasizes how probability informs statistical problems, thus helping readers develop an intuitive understanding of the statistical procedures commonly used by practicing engineers and scientists. Utilizing real data from actual studies across life science, engineering, computing and business, this useful introduction supports reader comprehension through a wide variety of exercises and examples. End-of-chapter reviews of materials highlight key ideas, also discussing the risks associated with the practical application of each material. In the new edition, coverage includes information on Big Data and the use of R. This book is intended for upper level undergraduate and graduate students taking a probability and statistics course in engineering programs as well as those across the biological, physical and computer science departments. It is also appropriate for scientists, engineers and other professionals seeking a reference of foundational content and application to these fields.

Principles and Methods for Data Science

  • 1st Edition
  • Volume 43
  • May 27, 2020
  • Arni S.R. Srinivasa Rao + 1 more
  • English
  • Hardback
    9 7 8 - 0 - 4 4 4 - 6 4 2 1 1 - 0
  • eBook
    9 7 8 - 0 - 4 4 4 - 6 4 2 1 2 - 7
Principles and Methods for Data Science, Volume 43 in the Handbook of Statistics series, highlights new advances in the field, with this updated volume presenting interesting and timely topics, including Competing risks, aims and methods, Data analysis and mining of microbial community dynamics, Support Vector Machines, a robust prediction method with applications in bioinformatics, Bayesian Model Selection for Data with High Dimension, High dimensional statistical inference: theoretical development to data analytics, Big data challenges in genomics, Analysis of microarray gene expression data using information theory and stochastic algorithm, Hybrid Models, Markov Chain Monte Carlo Methods: Theory and Practice, and more.

Mathematical Statistics with Applications in R

  • 3rd Edition
  • May 14, 2020
  • Kandethody M. Ramachandran + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 1 7 8 1 5 - 7
  • eBook
    9 7 8 - 0 - 1 2 - 8 1 7 8 1 6 - 4
Mathematical Statistics with Applications in R, Third Edition, offers a modern calculus-based theoretical introduction to mathematical statistics and applications. The book covers many modern statistical computational and simulation concepts that are not covered in other texts, such as the Jackknife, bootstrap methods, the EM algorithms, and Markov chain Monte Carlo (MCMC) methods, such as the Metropolis algorithm, Metropolis-Hastings algorithm and the Gibbs sampler. By combining discussion on the theory of statistics with a wealth of real-world applications, the book helps students to approach statistical problem-solving in a logical manner. Step-by-step procedure to solve real problems make the topics very accessible.

Financial, Macro and Micro Econometrics Using R

  • 1st Edition
  • Volume 42
  • January 20, 2020
  • Hrishikesh D. Vinod + 1 more
  • English
  • Hardback
    9 7 8 - 0 - 1 2 - 8 2 0 2 5 0 - 0
  • eBook
    9 7 8 - 0 - 1 2 - 8 2 0 2 5 1 - 7
Financial, Macro and Micro Econometrics Using R, Volume 42, provides state-of-the-art information on important topics in econometrics, including multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, financial market jumps and co-jumps, among other topics.

Fundamentals of Advanced Mathematics V3

  • 1st Edition
  • September 18, 2019
  • Henri Bourles
  • English
  • Hardback
    9 7 8 - 1 - 7 8 5 4 8 - 2 5 0 - 2
  • eBook
    9 7 8 - 0 - 0 8 - 1 0 2 3 8 6 - 0
Fundamentals of Advanced Mathematics, Volume Three, begins with the study of differential and analytic infinite-dimensional manifolds, then progresses into fibered bundles, in particular, tangent and cotangent bundles. In addition, subjects covered include the tensor calculus on manifolds, differential and integral calculus on manifolds (general Stokes formula, integral curves and manifolds), an analysis on Lie groups, the Haar measure, the convolution of functions and distributions, and the harmonic analysis over a Lie group. Finally, the theory of connections is (linear connections, principal connections, and Cartan connections) covered, as is the calculus of variations in Lagrangian and Hamiltonian formulations. This volume is the prerequisite to the analytic and geometric study of nonlinear systems.

Conceptual Econometrics Using R

  • 1st Edition
  • Volume 41
  • August 20, 2019
  • Hrishikesh D. Vinod + 1 more
  • English
  • Hardback
    9 7 8 - 0 - 4 4 4 - 6 4 3 1 1 - 7
  • eBook
    9 7 8 - 0 - 4 4 4 - 6 4 3 1 2 - 4
Conceptual Econometrics Using R, Volume 41 provides state-of-the-art information on important topics in econometrics, including quantitative game theory, multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, productivity and financial market jumps and co-jumps, among others.

Statistics for Biomedical Engineers and Scientists

  • 1st Edition
  • May 18, 2019
  • Andrew P. King + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 0 8 - 1 0 2 9 3 9 - 8
  • eBook
    9 7 8 - 0 - 0 8 - 1 0 2 9 4 0 - 4
Statistics for Biomedical Engineers and Scientists: How to Analyze and Visualize Data provides an intuitive understanding of the concepts of basic statistics, with a focus on solving biomedical problems. Readers will learn how to understand the fundamental concepts of descriptive and inferential statistics, analyze data and choose an appropriate hypothesis test to answer a given question, compute numerical statistical measures and perform hypothesis tests ‘by hand’, and visualize data and perform statistical analysis using MATLAB. Practical activities and exercises are provided, making this an ideal resource for students in biomedical engineering and the biomedical sciences who are in a course on basic statistics.

Biostatistics for Medical and Biomedical Practitioners

  • 2nd Edition
  • March 19, 2019
  • Julien I. E. Hoffman
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 1 7 0 8 4 - 7
  • eBook
    9 7 8 - 0 - 1 2 - 8 1 7 0 8 5 - 4
Basic Biostatistics for Medical and Biomedical Practitioners, Second Edition makes it easier to plan experiments, with an emphasis on sample size. It also shows what choices are available when simple tests are unsuitable and offers investigators an overview of how the kinds of complex tests that they won't do on their own work. The second edition presents a new, revised and enhanced version of the chapters, taking into consideration new developments and tools available, discussing topics, such as the basic aspects of statistics, continuous distributions, hypothesis testing, discrete distributions, probability in epidemiology and medical diagnosis, comparing means, regression and correlation. This book is a valuable source for students and researchers looking to expand or refresh their understanding of statistics as it applies to the biomedical and research fields. Based on the author’s 40+ years of teaching statistics to medical fellows and biomedical researchers across a wide range of fields, it is a valuable source for researchers who need to understand more about biostatistics to apply it to their work.

Related subjects

Probability theory and stochastic processes

Statistics