Cantitate/Preț
Produs
Total produse
Vezi coșul
Statistical Analysis and Data Display: An Intermediate Course with Examples in S-Plus, R, and SAS de Richard M. Heiberger

Statistical Analysis and Data Display: An Intermediate Course with Examples in S-Plus, R, and SAS: Springer Texts in Statistics

Autor Richard M. Heiberger, Burt Holland
en Limba Engleză Paperback – 19 noi 2010
1 Audience Students seeking master's degrees in applied statistics in the late 1960s and 1970s typically took a year-long sequence in statistical methods. Popular choices of the course text book in that period prior to the availability of high­ speed computing and graphics capability were those authored by Snedecor and Cochran, and Steel and Torrie. By 1980, the topical coverage in these classics failed to include a great many new and important elementary techniques in the data analyst's toolkit. In order to teach the statistical methods sequence with adequate coverage of topics, it became necessary to draw material from each of four or five text sources. Obviously, such a situation makes life difficult for both students and instructors. In addition, statistics students need to become proficient with at least one high-quality statistical software package. This book can serve as a standalone text for a contemporary year-long course in statistical methods at a level appropriate for statistics majors at the master's level or other quantitatively oriented disciplines at the doctoral level. The topics include both concepts and techniques developed many years ago and a variety of newer tools not commonly found in textbooks.
Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (2) 67687 lei  38-44 zile
  Springer – 20 mar 2019 67687 lei  38-44 zile
  Springer – 19 noi 2010 119337 lei  6-8 săpt.
Hardback (1) 95795 lei  38-44 zile
  Springer – 24 dec 2015 95795 lei  38-44 zile

Din seria Springer Texts in Statistics

  • All of Statistics: A Concise Course in Statistical Inference
    Preț: 42181 lei
  • 18% Applied Probability
    Preț: 86856 lei
  • 18% Statistical Modeling and Computation
    Preț: 71435 lei
  • Probability Theory: Independence, Interchangeability, Martingales
    Preț: 48134 lei
  • 15% Log-Linear Models and Logistic Regression
    Preț: 62948 lei
  • 15% Testing Statistical Hypotheses
    Preț: 71754 lei
  • 15% A First Course in Bayesian Statistical Methods
    Preț: 46173 lei
  • 18% Time Series Analysis and Its Applications: With R Examples
    Preț: 87630 lei
  • 18% Generalized Linear Models With Examples in R
    Preț: 68398 lei
  • 18% Matrix Algebra: Theory, Computations and Applications in Statistics
    Preț: 72343 lei
  • 13% An Introduction to Statistical Learning: with Applications in Python
    Preț: 51654 lei
  • 18% Monte Carlo Statistical Methods
    Preț: 108281 lei
  • 15% Statistics for Bioengineering Sciences: With MATLAB and WinBUGS Support
    Preț: 65073 lei
  • Time Series Analysis: With Applications in R
    Preț: 45905 lei
  • 18% A Course in Mathematical Statistics and Large Sample Theory
    Preț: 81936 lei
  • 15% A Modern Approach to Regression with R
    Preț: 57289 lei
  • 20% Probability via Expectation
    Preț: 83714 lei
  • 18% Modern Mathematical Statistics with Applications
    Preț: 69476 lei
  • 18% Applied Bayesian Statistics
    Preț: 85391 lei
  • 15% An Introduction to Statistical Learning
    Preț: 39557 lei
  • A Modern Introduction to Probability and Statistics: Understanding Why and How
    Preț: 28386 lei
  • 18% All of Nonparametric Statistics
    Preț: 91149 lei
  • 15% Probability and Statistical Inference: Volume 2: Statistical Inference
    Preț: 62575 lei
  • 18% Statistical Methods: The Geometric Approach
    Preț: 71769 lei
  • Introduction to Statistics: The Nonparametric Way
    Preț: 38804 lei
  • Mathematical Statistics: A Unified Introduction
    Preț: 38840 lei
  • Basic Principles of Structural Equation Modeling: An Introduction to LISREL and EQS
    Preț: 37971 lei
  • 15% Stat Labs: Mathematical Statistics Through Applications
    Preț: 55638 lei
  • 18% An Introduction to Bayesian Analysis: Theory and Methods
    Preț: 96226 lei
  • 15% Probability
    Preț: 67540 lei
  • Fundamentals of Mathematical Statistics: Probability for Statistics
    Preț: 39154 lei
  • 18% Statistical Design
    Preț: 86113 lei
  • 15% The Bayesian Choice: From Decision-Theoretic Foundations to Computational Implementation
    Preț: 57764 lei
  • 23% Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning
    Preț: 74110 lei
  • 19% Testing Statistical Hypotheses
    Preț: 58770 lei
  • 15% Theory of Point Estimation
    Preț: 63077 lei
  • 15% Statistical Analysis of Financial Data in S-Plus
    Preț: 65652 lei
  • Probability for Statisticians
    Preț: 40706 lei
  • 15% Measure Theory and Probability Theory
    Preț: 57764 lei
  • 18% Applied Multivariate Analysis
    Preț: 78288 lei
  • Advanced Linear Modeling: Multivariate, Time Series, and Spatial Data; Nonparametric Regression and Response Surface Maximization
    Preț: 38747 lei
  • Analyzing Categorical Data
    Preț: 39302 lei
  • 18% Applied Regression Analysis: A Research Tool
    Preț: 73012 lei

Preț: 119337 lei

Preț vechi: 145533 lei
-18% Nou

Puncte Express: 1790
Preț estimativ în valută:
21116€ • 24796$ • 18535£

Carte tipărită la comandă

Livrare economică 27 ianuarie-10 februarie 26

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă
Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9781441923202
ISBN-10: 1441923209
Pagini: 756
Ilustrații: XXIV, 730 p.
Dimensiuni: 178 x 254 x 40 mm
Greutate: 1.29 kg
Ediția:Softcover reprint of the original 1st ed. 2004
Editura: Springer
Colecția Springer
Seria Springer Texts in Statistics

Locul publicării:New York, NY, United States

Public țintă

Research

Cuprins

1 Introduction and Motivation.- 2 Data and Statistics.- 3 Statistics Concepts.- 4 Graphs.- 5 Introductory Inference.- 6 One-Way Analysis of Variance.- 7 Multiple Comparisons.- 8 Linear Regression by Least Squares.- 9 Multiple Regression—More Than One Predictor.- 10 Multiple Regression—Dummy Variables and Contrasts.- 11 Multiple Regression—Regression Diagnostics.- 12 Two-Way Analysis of Variance.- 13 Design of Experiments—Factorial Designs.- 14 Design of Experiments—Complex Designs.- 15 Bivariate Statistics—Discrete Data.- 16 Nonparametrics.- 17 Logistic Regression.- 18 Time Series Analysis.- A Software.- A.1 Statistical Software.- A.2 Text Editing Software.- A.2.1 Emacs.- A.2.2 Microsoft Word.- A.3 Word Processing Software.- A.3.2 Microsoft Word.- A.4 Graphics Display Software.- A.5 Operating Systems.- A.6 Mathematical Fonts.- A.7 Directory Structure.- A.7.1 HOME Directory.- A.7.2 HH Book Online Files.- B.1 Create Your Working Directory and Make the HH Library Available.- B.1.3 Windows and R.- B.1.6 Unix and R.- B.4 HH Library Functions.- B.5 Learning the S Language.- B.6 S Language Style.- C SAS.- C.1 Make the HH Library Available.- C.1.1 Windows.- C.1.2 Unix.- C.2 Using SAS with HH.- C.2.1 Reading HH Datasets.- C.2.2 Any Other Data Files.- C.2.3 ASCII Data Files with TAB Characters.- C.2.4 Windows and Unix EOL (End-of-Line) Conventions.- C.3 Macros.- C.4 Learning the SAS Language.- C.5 SAS Coding Conventions.- D Probability Distributions.- D.1.1 An Example Involving Calculations with the Binomial Distribution.- D.2 Noncentral Probability Distributions.- E Editors.- E.1 Working Style.- E.2 Typography.- E.3 Emacs and ESS.- E.3.1 ESS.- E.3.2 Mouse and Keyboard.- E.3.3 Learning Emacs.- E.3.4 Requirements.- E.4 Microsoft Word.- E.4.1 Learning Word.- E.4.2Requirements 6.- E.5 Microsoft Excel.- E.5.1 Database Management.- E.5.2 Organizing Calculations.- E.5.3 Excel as a Statistical Calculator.- E.6 Exhortations, Some of Which Are Writing Style.- E.6.1 Writing Style.- E.6.2 Programming Style and Common Errors.- E.6.3 Presentation of Results.- F Mathematics Preliminaries.- F.1 Algebra Review.- F.2 Elementary Differential Calculus.- F.3 An Application of Differential Calculus.- F.4 Topics in Matrix Algebra.- F.4.1 Elementary Operations.- F.4.2 Linear Independence.- F.4.3 Rank.- F.4.4 Quadratic Forms.- F.4.5 Orthogonal Transformations.- F.4.6 Orthogonal Basis.- F.4.8 Matrix Factorization—Cholesky.- F.4.9 Orthogonal Polynomials.- F.4.10 Projection Matrices.- F.4.11 Geometry ot Mlatrices.- F.4.12 Eigenvalues and Eigenvectors.- F.4.13 Singular Value Decomposition.- F.4.14 Generalized Inverse.- F.4.15 Solving Linear Equations.- F.5 Combinations and Permutations.- F.5.1 Factorial.- F.5.2 Permutations.- F.5.3 Combinations.- F.6 Exercises.- G Graphs Based on Cartesian Products.- G.1 Structured Sets of Graphs.- G.1.1 Cartesian Products.- G.1.2 Trellis Paradigm.- G.2 Scatterplot Matrices: splom and xysplom.- G.3 Cartesian Products of Sets of Functions.- G.4 Graphs Requiring Multiple Calls to xysplom.- G.5 Asymmetric Roles for the Row and Column Sets.- G.6 Rotated Plots.- G.7 Squared Residual Plots.- G.8 Alternate Presentations.- References.- List of Datasets.

Recenzii

From the reviews:
"Heiberger and Holland have produced a comprehensive, well-presented review of essential statistical topics...this is an excellent book for suppporting advanced undergraduate courses on statsitics or data analysis [and] a valuable reference source to researchers..." Biomedical Engineering Online, 2005, 4:18
"Overall, I am impressed with this book and recommend it for graduate statistical methods courses where S-PLUS, R, or SAS is used. There is good incorporation of software tools that complement the statsitical methods presented that go beyond what most statistical methods books provide, a very broad range of topics is covered with examples representing many disciplines, and the emphasis of graphing and presentation of data is excellent." Technometrics, August 2005
"Discussion of each topic begins with a clear and easy-to-read presentation of the relevant theory at a level that statistics majors (and nonmajors) would enjoy..." The American Statistician, August 2005
"Throughout the book, statistical theory is kept to a minimum, and statistical concepts and methods are well stated, without lengthy derivations of formulas, but with the aid of graphical displays. Many examples are provided to illustrate the use of statistical methods. Exercise problems are well written and will be good practice for readers." Biometrics, December 2005
"A notable aspect of this book is the strong emphasis given to presenting data using graphical displays as well as the instructions and programs provided to create these displays in … . The authors’ great emphasis on graphical methods … of the existing statistical methods books. I am impressed with this book and recommend it for graduate statistical methods courses where S-PLUS, R, or SAS is used. There is good incorporation of software tools …. The emphasis of graphing and presentation of data is excellent." (Theresa L. Utlaut,Technometrics, Vol. 47 (3), August, 2005)
"The statistical analysis in the book is taught on interesting real examples. … the analysis is quite deep. An extraordinary care is devoted to graphical presentation of results. Many of the graphical formats are novel. … appendices to the book contain useful remarks on statistical software, typography, and a review of fundamental mathematical concepts. A reader who studies the book and repeats the authors’ calculations gains basic statistical skill and knowledge of software for solving similar problems in applications." (EMS - European Mathematical Society Newsletter, December, 2004)
"This is a huge book with huge aims – and the authors managed to get it done. … is a modern textbook on many statistical methods including theory, with many well selected examples, and with code written for appropriate statistical software … . It is nice to see a book that tries to explain methods together with the usage of two widely used statistical software systems, namely SAS and the S language. This comprehensive book is a nice all rounder for statistics students … ." (Uwe Ligges, Statistical Papers, Vol. 47, 2005)
"Although this book is aimed at postgraduate students, it would be equally valuable for non-specialists … . This book is a review of the most widely used areas of statistics … . A good feature of this book is that all the datasets used are freely available in online files … . Therefore, it is possible to carry out the analyses yourself … . There are many examples, which are well chosen to illustrate the points being made." (D. A. Goodwin, Journal of Applied Statistics, Vol. 33 (7), August, 2006)
"The authors present the book as a ‘standalone text for a contemporary year-long course in statistical methods’ … . the core material is of high standard, and the book also brings scientific contributions in terms of novel graph types. … my overall impression of the book isvery good. I believe that the authors have managed to balance innovativeness and accessibility … . it is both a valid textbook for students and teachers alike, and a useful reference book for practitioners." (Gaj Vidmar, ISCB News, Issue 41, June, 2006)

Textul de pe ultima copertă

This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data—showing code, graphics, and accompanying computer listings—for all the methods they cover. They emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how accompanying traditional tabular results are used to confirm the visual impressions derived directly from the graphs. Many of the graphical formats are novel and appear here for the first time in print. All chapters have exercises.
This book can serve as a standalone text for statistics majors at the master's level and for other quantitatively oriented disciplines at the doctoral level, and as a reference book for researchers. In-depth discussions of regression analysis, analysis of variance, and design of experiments are followed by introductions to analysis of discrete bivariate data, nonparametrics, logistic regression, and ARIMA time series modeling. The authors illustrate classical concepts and techniques with a variety of case studies using both newer graphical tools and traditional tabular displays.
The authors provide and discuss S-Plus, R, and SAS executable functions and macros for all new graphical display formats. All graphs and tabular output in the book were constructed using these programs. Complete transcripts for all examples and figures are provided for readers to use as models for their own analyses.
Richard M. Heiberger and Burt Holland are both Professors in the Department of Statistics at Temple University and elected Fellows of the American Statistical Association. Richard M. Heiberger participated in the design of the S-Plus linear model and analysis of variance commands while on research leave at Bell Labs in 1987–88 and has been closely involved as a beta tester and user of S-Plus. Burt Hollandhas made many research contributions to linear modeling and simultaneous statistical inference, and frequently serves as a consultant to medical investigators. Both teach the Temple University course sequence that inspired them to write this text.

Caracteristici

Provides and discusses S-PLUS, R, and SAS executable functions and macros for all new graphical display formats All graphs and tabular output in the book were constructed using these programs

Notă biografică

Richard M. Heiberger is Professor Emeritus in the Department of Statistics of Temple University, an elected Fellow of the American Statistical Association, and a former Chair of the Section on Statistical Computing of the American Statistical Association.  He was Graduate Chair for the Department of Statistics and Acting Associate Vice Provost for the University.  He participated in the design of the linear model and analysis of variance functions while on research leave at Bell Labs.  He has taught short courses at the Joint Statistics Meetings, the American Statistical Association Conference on Statistical Practice, the R Users Conference, and the Deming Conference on Applied Statistics.  He has consulted with several pharmaceutical companies.
Burt Holland was Professor in the Department of Statistics of Temple University, an elected Fellow of the American Statistical Association, Chair of the Department of Statistics of Temple University, and Chair of Collegial Assembly of the Fox School.  He has taught short courses at the Joint Statistics Meetings and the Deming Conference on Applied Statistics.  He has made many contributions to linear modeling and simultaneous statistical inference.  He frequently served as consultant to medical investigators.  He developed a very popular General Education course on Statistics and the News.