Introduction to the Practice of Statistics
Author : David S. Moore
Publisher : W.H. Freeman
Page : 908 pages
File Size : 11,41 MB
Release : 1993
Category : Mathematics
ISBN : 9780716722502
Author : David S. Moore
Publisher : W.H. Freeman
Page : 908 pages
File Size : 11,41 MB
Release : 1993
Category : Mathematics
ISBN : 9780716722502
Author : Tilman M. Davies
Publisher : No Starch Press
Page : 833 pages
File Size : 22,4 MB
Release : 2016-07-16
Category : Computers
ISBN : 1593276516
The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.
Author : G. Jay Kerns
Publisher : Lulu.com
Page : 388 pages
File Size : 14,26 MB
Release : 2010-01-10
Category : Education
ISBN : 0557249791
This is a textbook for an undergraduate course in probability and statistics. The approximate prerequisites are two or three semesters of calculus and some linear algebra. Students attending the class include mathematics, engineering, and computer science majors.
Author : Patrick W. Shannon
Publisher :
Page : 696 pages
File Size : 31,3 MB
Release : 2002
Category : Business & Economics
ISBN :
This book presents core topics in descriptive and inferential statistics with a rich assortment of business examples and real data, and an emphasis on decision-making. It contains a narrative writing style-and the captivating examples and applications, and rich data sets are woven right into the narrative. The examples are interesting, realistic and drawn from all areas of business and life. There is significant emphasis on using statistical software as a tool, with most examples presented in a spreadsheet environment using Excel and Minitab. Every topic is introduced in the context of a real business application complete with real data, from small and large data sets.
Author : David S. Moore
Publisher : W H Freeman & Company
Page : 825 pages
File Size : 43,17 MB
Release : 1999
Category : Mathematics
ISBN : 9780716735021
CD-ROM includes: Electronic Encyclopedia of Statistical Examples and Exercises, an interactive quiz for each chapter, video clips and some special electronic statistical tools.
Author : Douglas C. Montgomery
Publisher : Wiley Global Education
Page : 771 pages
File Size : 43,39 MB
Release : 2019-11-06
Category : Technology & Engineering
ISBN : 1119399297
Once solely the domain of engineers, quality control has become a vital business operation used to increase productivity and secure competitive advantage. Introduction to Statistical Quality Control offers a detailed presentation of the modern statistical methods for quality control and improvement. Thorough coverage of statistical process control (SPC) demonstrates the efficacy of statistically-oriented experiments in the context of process characterization, optimization, and acceptance sampling, while examination of the implementation process provides context to real-world applications. Emphasis on Six Sigma DMAIC (Define, Measure, Analyze, Improve and Control) provides a strategic problem-solving framework that can be applied across a variety of disciplines. Adopting a balanced approach to traditional and modern methods, this text includes coverage of SQC techniques in both industrial and non-manufacturing settings, providing fundamental knowledge to students of engineering, statistics, business, and management sciences. A strong pedagogical toolset, including multiple practice problems, real-world data sets and examples, and incorporation of Minitab statistics software, provides students with a solid base of conceptual and practical knowledge.
Author : Jane C. Miller
Publisher : Ellis Horwood Limited
Page : 227 pages
File Size : 22,87 MB
Release : 1992
Category : Chemistry, Analytic
ISBN : 9780138454210
Author : Douglas Altman
Publisher : John Wiley & Sons
Page : 322 pages
File Size : 30,53 MB
Release : 2013-06-03
Category : Medical
ISBN : 1118702506
This highly popular introduction to confidence intervals has been thoroughly updated and expanded. It includes methods for using confidence intervals, with illustrative worked examples and extensive guidelines and checklists to help the novice.
Author : Brigitte Baldi
Publisher : Macmillan Higher Education
Page : 756 pages
File Size : 41,25 MB
Release : 2013-12-15
Category : Mathematics
ISBN : 1464133212
This remarkably engaging textbook gives biology students an introduction to statistical practice all their own. It covers essential statistical topics with examples and exercises drawn from across the life sciences, including the fields of nursing, public health, and allied health. Based on David Moore’s The Basic Practice of Statistics, PSLS mirrors that #1 bestseller’s signature emphasis on statistical thinking, real data, and what statisticians actually do. The new edition includes new and updated exercises, examples, and samples of real data, as well as an expanded range of media tools for students and instructors.
Author : Kandethody M. Ramachandran
Publisher : Elsevier
Page : 825 pages
File Size : 11,85 MB
Release : 2014-09-14
Category : Mathematics
ISBN : 012417132X
Mathematical Statistics with Applications in R, Second 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 the 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.This book provides a step-by-step procedure to solve real problems, making the topic more accessible. It includes goodness of fit methods to identify the probability distribution that characterizes the probabilistic behavior or a given set of data. Exercises as well as practical, real-world chapter projects are included, and each chapter has an optional section on using Minitab, SPSS and SAS commands. The text also boasts a wide array of coverage of ANOVA, nonparametric, MCMC, Bayesian and empirical methods; solutions to selected problems; data sets; and an image bank for students.Advanced undergraduate and graduate students taking a one or two semester mathematical statistics course will find this book extremely useful in their studies. - Step-by-step procedure to solve real problems, making the topic more accessible - Exercises blend theory and modern applications - Practical, real-world chapter projects - Provides an optional section in each chapter on using Minitab, SPSS and SAS commands - Wide array of coverage of ANOVA, Nonparametric, MCMC, Bayesian and empirical methods