Statistics with Maple is a practical guide for engineers, statisticians, business professionals and others who use the Maple software package and who wish to use it to produce numerical summaries, make graphical displays, and perform statistical inference. The book and software package is unique in its focus on using Maple for statistical methodology.
This tutorial and reference manual assumes that readers have a basic knowledge of statistics and a familiarity with Maple.
Sprache
Verlagsort
Verlagsgruppe
Elsevier Science Publishing Co Inc
Zielgruppe
Maße
Höhe: 235 mm
Breite: 191 mm
Gewicht
ISBN-13
978-0-12-041556-4 (9780120415564)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Martha L. Abell and James P. Braselton are graduates of the Georgia Institute of Technology and the Ohio State University, respectively, and teach at Georgia Southern University, Statesboro where they have extensive experience instructing students at both the undergraduate and graduate levels. Other books by the authors include Differential Equations with Mathematica and Mathematica by Example. Martha L. Abell and James P. Braselton are graduates of the Georgia Institute of Technology and the Ohio State University, respectively, and teach at Georgia Southern University, Statesboro where they have extensive experience instructing students at both the undergraduate and graduate levels. Other books by the authors include Differential Equations with Mathematica and Mathematica by Example.
Autor*in
Georgia Southern University, Statesboro, U.S.A.
Professor Emerita
Associate Professor Emeritus
Working With Maple; Data and Data File Manipulation; Univariate Methods for Describing Data; Multivariate Methods for Describing Data; Tabular and Graphical Methods for Presenting Data; Data Smoothing and Time Series An Introduction; Probability and Probability Distributions; Random Number Generation and Simulation; One and Two Sample Inferential Procedures; Analysis of Variance and Multiple Comparisons of Means; Diagnostic Procedures and Transformations; Regression and Correlation; Nonparametric Methods