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Samples & Populations: Data & Statistics
Samples & Populations: Data & Statistics
Publisher: Pearson/Prentice Hall | pages: 93 | 2006 | ISBN: 0131656589 | PDF | 14,4 mb
The unit will involve the process of statistical investigation. As part of this process, we will pay special attention to the ways that data are collected. This unit begins with tools for grouping data and comparing distributions. Then students explore what samples are and how they are related to populations, ways to select samples, and the use of random samples. Finally, students look at relationships between two attributes and what it means to say that information about values from one attribute can be used to understand, explain, or predict values of another attribute.
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Understanding Basic Statistics
Author(s): Charles Henry Brase, Corrinne Pellillo Brase
Publisher: Brooks Cole, 4 edition
Date : 2006
Pages : 526
Format : pdf
OCR :
Quality :
Language : English
ISBN-10 : 0618632271
ISBN-13 : 9780618632275
Product Description
A condensed, streamlined version of the popular, widely used Understandable Statistics, 8/e, this text offers instructors an effective solution to teaching the essentials of statistics within a shorter time frame. Designed to help students overcome their apprehension about statistics, Understanding Basic Statistics, 4/e is a thorough, accessible text that demonstrates the applicability of statistics in the real world. Student-friendly highlights of the Fourth Edition include solutions and key steps to odd-numbered problems, highlighted definitions, Expand Your Knowledge and Cumulative Review Problems, and a complete technology package with additional learning opportunities and skills-reinforcement exercises.
About the Author
Charles Brase has more than 30 years of full-time teaching experience in mathematics and statistics. He taught at the University of Hawaii, Manoa Campus, for several years and at Regis University in Denver, Colorado, for more than 28 years. Charles received the Excellence in Teaching award from the University of Hawaii and the Faculty Member of the Year from Regis University on two occasions. He earned degrees from the University of Colorado, Boulder, and has a Ph.D. in Mathematics, an M.A. in Mathematics, and a B.A. in Physics.
Corrinne has taught at Hawaii Pacific College, Honolulu Community College, and Arapahoe Community College in Littleton, Colorado. She was also involved in the mathematics component of an equal opportunity program at the University of Colorado. Corrinne received the Faculty of the Year award from Arapahoe Community College. She earned degrees from the University of Colorado, Boulder, and has an M.A. and B.A. in Mathematics.
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A Guide to Doing Statistical Analysis in Second Language Research Using SPSS
Jenifer Larson-Hall, "A Guide to Doing Statistical Analysis in Second Language Research Using SPSS"
Routledge | 2009 | ISBN: 0805861866, 0805861858 | 426 pages | PDF | 5,1 MB
This valuable book shows second language researchers how to use the statistical program SPSS to conduct statistical tests frequently done in SLA research. Using data sets from real SLA studies, A Guide to Doing Statistics in Second Language Research Using SPSS shows newcomers to both statistics and SPSS how to generate descriptive statistics, how to choose a statistical test, and how to conduct and interpret a variety of basic statistical tests. The author covers the statistical tests that are most commonly used in second language research, including chi-square, t-tests, correlation, multiple regression, ANOVA and non-parametric analogs to these tests. The text is abundantly illustrated with graphs and tables depicting actual data sets, and exercises throughout the book help readers understand concepts (such as the difference between independent and dependent variables) and work out statistical analyses. Answers to all exercises are provided on the book’s companion website, along with sample data sets and other supplementary material.
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كتاب : Elementary Statistics Using JMP (With Examples Code)
Sandra D. Schlotzhauer "Elementary Statistics Using JMP (With Examples Code)"
April 2007 | English | ISBN-13: 978-1-59994-375-6 | 475 Pages | PDF | 5.20 MBLearn how to perform basic statistical analyses using the powerful JMP software. This reader-friendly guide bridges the gap between statistics texts and JMP documentation. Author Sandra Schlotzhauer opens with an explanation of the basics of JMP data tables, demonstrating how to use JMP for descriptive statistics and graphs. The author continues with a lucid discussion of fundamental statistical concepts, including normality and hypothesis testing. Using a step-by-step approach, she shows analyses for comparing two groups, comparing multiple groups, fitting regression equations, and exploring contingency tables. For each analysis, the author clearly explains assumptions, the statistical approach, the JMP steps and results, and how to make conclusions from the results.
Statistical methods include:
* histograms, box plots, descriptive statistics, stem-and-leaf plots
* mosaic plots, bar charts, and treemaps
* t-tests and Wilcoxon tests to compare two independent or paired groups
* one-way ANOVA and Kruskal-Wallis tests, and selected multiple comparison techniques
* Pearson and Spearman correlation coefficients
* regression models for lines, curves, and multiple variables
* residuals plots and lack-of-fit tests for regression
* Chi-square tests, Fisher's Exact test, and measures of association for contingency tables.
Understand how to interpret both the graphs and text reports, as well as how to customize JMP results to meet your needs. Packed with examples from a broad range of industries, this text is ideal for novice to intermediate JMP users. Prior statistical knowledge, JMP experience, or programming skills are not required.
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Computational Statistics
James E. Gentle "Computational Statistics"
Jul 2009 | English | ISBN-13: 978-0-387-98143-7 | 721 Pages | PDF | 6.38 MBComputational inference has taken its place alongside asymptotic inference and exact techniques in the standard collection of statistical methods. Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional properties of estimators and test statistics. This book describes computationally-intensive statistical methods in a unified presentation, emphasizing techniques, such as the PDF decomposition, that arise in a wide range of methods.
The book assumes an intermediate background in mathematics, computing, and applied and theoretical statistics. The first part of the book, consisting of a single long chapter, reviews this background material while introducing computationally-intensive exploratory data analysis and computational inference.
The six chapters in the second part of the book are on statistical computing. This part describes arithmetic in digital computers and how the nature of digital computations affects algorithms used in statistical methods. Building on the first chapters on numerical computations and algorithm design, the following chapters cover the main areas of statistical numerical analysis, that is, approximation of functions, numerical quadrature, numerical linear algebra, solution of nonlinear equations, optimization, and random number generation.
The third and fourth parts of the book cover methods of computational statistics, including Monte Carlo methods, randomization and cross validation, the bootstrap, probability density estimation, and statistical learning.
The book includes a large number of exercises with some solutions provided in an appendix.
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بارك الله فيك أخي alialobeidy وفقك الله وانار دربك وسبيلك وزادك علماً
Manual on Presentation of Data and Control Chart Analysis, 7th Edition
Manual on Presentation of Data and Control Chart Analysis, 7th Edition Summary:
By ASTM Committee E-11 on Quality and Stati
* Publisher: ASTM International
* Number Of Pages: 135
* Publication Date: 2002-02
* ISBN-10 / ASIN: 0803120931
* ISBN-13 / EAN: 9780803120938
Product Description:
This comprehensive manual assists in the development of supportive data and analysis when preparing standard test methods, specifications, and practices. It provides the latest information regarding statistical and quality control methods and their applications. This is the 7th revision of this popular manual first published in 1933 as STP 15 and is an excellent teaching and reference tool for data analysis and complements work needed for ISOquality control requirements.
PART 1 discusses frequency distributions, simple statistical measures, and the presentation in concise form, of the essential information contained in a single set of n observations.
PART 2 examines the problem of expressing limits of uncertainty for various statistical measures, together with some working rules for rounding-off observed results to an appropriate number of significant figures.
Part 3 covers the control chart method for the analysis of observational data obtained from a series of samples, and for detecting lack ofstatistical control of quality.
New material includes:
Discussions of whole number frequency distributions, empirical percentiles, and order statistics.
Additional material focusing on the risks involved in the decision-making process based on data; and tests for assessing evidence of nonrandom behavior in process control charts.
The use of the s(rms) statistic has been minimized in favor of the sample standard deviation to reduce confusion as to their use.
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A Handbook of Statistical Analyses Using R, Second Edition
A Handbook of Statistical Analyses Using R, Second Edition
Publisher: Chapman & Hall/CRC | Pages: 376 | 2009-07-20 | ISBN 1420079336 | PDF | 4 MB
A Proven Guide for Easily Using R to Effectively Analyze Data
Like its bestselling predecessor, A Handbook of Statistical Analyses Using R, Second Edition provides a guide to data analysis using the R system for statistical computing. Each chapter includes a brief account of the relevant statistical background, along with appropriate references.
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Probability and Real Trees: Ecole d'Été de Probabilités de Saint-Flour XXXV-2005
Steven N. Evans, "Probability and Real Trees: Ecole d'Été de Probabilités de Saint-Flour XXXV-2005 "
Springer | 2007 | ISBN: 3540747974 | 200 pages | PDF | 10,7 MB
Random trees and tree-valued stochastic processes are of particular importance in combinatorics, computer science, phylogenetics, and mathematical population genetics. Using the framework of abstract "tree-like" metric spaces (so-called real trees) and ideas from metric geometry such as the Gromov-Hausdorff distance, Evans and his collaborators have recently pioneered an approach to studying the asymptotic behaviour of such objects when the number of vertices goes to infinity. These notes survey the relevant mathematical background and present some selected applications of the theory.
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متشكرييييييييييييييييييين اكتيييييييير اخي الكريم
يمنع وضع صور الفنانين والفنانات
العفو وفقكم الله
SPSS Programming and Data Management, 2nd Edition
Author(s): Raynald Levesque
Publisher: SPSS Inc.
Date : 2005
Pages : 390
Format : PDF
OCR :
Quality : Perfect
Language : English
ISBN-10 : 156827355X
ISBN-13 :
Experienced data analysts know that a successful analysis or meaningful report often
requires more work in acquiring, merging, and transforming data than in specifying the
analysis or report itself. SPSS contains powerful tools for accomplishing and
automating these tasks. While much of this capability is available through the graphical
user interface, many of the most powerful features are available only through command
syntax, the macro facility that extends the power of command syntax, and the scripting
facility. Until now, no book or other documentation has focused on those features, and
many potential users have been unaware of the power available to them or have not
exploited it for lack of examples. This book fills that void.
link
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Applied Statistics and Probability for Engineers, Third Edition
Author(s): Douglas C. Montgomery and George C. Runger
Publisher: Wiley, John & Sons
Date : 2003
Pages : 720
Format : ISO
OCR :
Quality : Perfect
Language : English
ISBN-10 :
ISBN-13 : 9780471735564
This best-selling engineering statistics text provides a practical approach that is more oriented to engineering and the chemical and physical sciences than many similar texts. It's packed with unique problem sets that reflect realistic situations engineers will encounter in their working lives.
Each copy of the book includes an e-Text on CD - that is a complete electronic version of book. This e-Text features enlarged figures, worked-out solutions, links to data sets for problems solved with a computer, multiple links between glossary terms and text sections for quick and easy reference, and a wealth of additional material to create a dynamic study environment for students.
Suitable for a one- or two-term Jr/Sr course in probability and statistics for all engineering majors.
Table of Contents
1. The Role of Statistics in Engineering
2. Probability
3. Discrete Random Variables and Probability Distributions
4. Continuous Random Variables and Probability Distributions
5. Joint Probability Distributions
6. Random Sampling and Data Description
7. Point Estimation of Parameters
8. Statistical Intervals for a Single Sample
9. Tests of Hypotheses for a Single Sample
10. Statistical Inference for Two Samples
11. Simple Linear Regression and Correlation
12. Multiple Linear Regression
13. Design and Analysis of Single-Factor Experiments: The Analysis of Variance
14. Design of Experiments with Several Factors
15. Nonparametric Statistics
16. Statistical Quality Control
Appendix A: Statistical Tables & Charts
Appendix B: Bibliography
Appendix C: Answers to Selected Exercises
New to this Edition
Problems, examples, and exercises have all been thoroughly updated to reflect today's engineering realities.
Examples and exercises are drawn from more diverse fields such as bioengineering, environmental sciences, and computer science.
Interactive e-Text format. Includes data sets, select worked-out solutions, enlarged figures, and multiple links between glossary terms and text sections for quick and easy reference.
Hallmark Features
More Motivation. A completely revised chapter 1 gets students motivated right from the beginning.
Revised Probability Topics. The authors have revised and enhanced probability topics to promote even easier understanding.
Chapter Reorganization. Chapters on hypothesis testing and confidence intervals have been reorganized and rewritten. There is now expanded treatment of confidence intervals, prediction intervals, and tolerance intervals.
Real Engineering Applications. Treatment of all topics is oriented towards real engineering applications. In the probability chapters, the authors do not emphasize counting methods or artificial applications such as gambling.
Real Data, Real Engineering Situations. Examples and exercises throughout text use real data and real engineering situations. This motivates students to learn new concepts and gives them a taste of practical engineering experience.
Use of the Computer. Computer usage is closely integrated into the text and homework exercises.
Supplements
Instructor's Resource on CD-ROM
0-471-23104-5
Available to instructors adopting this text for their course. Contains solutions to all problems in the text, data sets in Minitab, Excel, and text format for exercises in the text that may be solved using computational software, and illustrations from the text in jpeg format for easy import to PowerPoint.
All of these resources are also available on the password-protected Instructor Companion Site. Click on the Instructor Companion Site at the left to request a password to access these resources online.
eGrade Online Assessment
eGrade is an online problem-solving, quizzing, and testing tool. The engineering statistics eGrade testbank contains 400 problems selected from the text. At least 50% of the questions are randomized, so students will receive problems that are constantly refreshed.
eGrade
An eGrade test bank is available with this title. Assign, deliver and grade homework, quizzes, and exams automatically using eGrade's web-based software!
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MINITAB Student Release 12
0-471-31501-X
Student Version of the powerful MINITAB statistical software may be purchased in a set with the Montgomery text. Use ISBN 0-471-28152-2 to order the set of the text with software for your course.
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Introduction to Mathematical Statistics, 4th Edition
Author(s): Robert V. Hogg, Allen T. Craig
Publisher: Macmillan USA
Date : 1978
Pages : 448
Format : PDF
OCR :
Quality : Very Good
Language : English
ISBN-10 :
ISBN-13 : 9780023557101
This classic book retains its outstanding ongoing features and continues to provide readers with excellent background material necessary for a successful understanding of mathematical statistics. Chapter topics cover classical statistical inference procedures in estimation and testing, and an in-depth treatment of sufficiency and testing theory—including uniformly most powerful tests and likelihood ratios. Many illustrative examples and exercises enhance the presentation of material throughout the book. For a more complete understanding of mathematical statistics.
Review:
Obtuse and error-riddled
There are many great math texts that are difficult going at first, but which pay great dividends the more you “drill down” into them. While this may have been the case with previous editions of this text, the crazy-making number of errata in this edition make it very difficult going ALWAYS.
Furthermore, the ease and small number of exercises aren’t enough to get the concepts firmly stuck in your cranium. I’m using three other supplements to get me through my graduate probability/stats sequence. Pbbtt!!
Review:
Needs to be re-edited
This is one of the worst textbooks that I have ever used in my life. Everyone in my class of over twenty people hated this book. Even my teacher did not think it was very good but unfortunately it is a standard text for graduate level statistics. This book needs more examples and to be edited better as there are a good bit of errors. Also, the structure of the book needs to be changed to be more user friendly. The reader should not have to struggle so much to find the information that he is looking for.
The subject matter in the book is powerful and useful. However, a good textbook displays the information in an accessible way and this book does not do that.
Review:
Not a good teaching tool. Not to mention, full of typos and inconsistencies.
Much too wordy and difficult to read. Not nearly enough examples structured like the exercises at the end of each chapter. Need to more adequately prove concepts/show origins of concepts (i.e. more than just “this is what it is, uh, because it is” or “because that’s how it works out best”). Many typos, so you don’t know what to “trust” (even one of the tables in the appendix has incorrect values for one of the columns in some printings). Not a good textbook for “self-teaching,” hope you have a good professor to learn from.
Review:
Not introductory at all
The book is not introductory to students outside statistics dept or engineering depts. There are logic jumps everywhere and the author doesn’t even bother to briefly explain every concept at the beginning of each section, not mention to tell us how to apply this concept in a real situation. This is a required book in a class I am taking. The only reason I bought it is because I got it very cheap. However, I notice that most students in my class don’t bother read the book, even student from statistics dept. We basically highly depend on lecture notes, homework solutions, and old exam questions. This is the worst book I read ever. I hope there are some other books out there which do a better job to connect math statistics to real situation.
Review:
Yes, it is one of the best books in statistics, although it is not “introductory”
This is one of the most famous books on mathematical statistics. Is it good though? Many reviewers think not. My own personal opinion is that it is fantastic and extremely carefully written. The sixth edition has been completely modernized and includes such “modern” topics as MCMC, robust methods and the EM algorithm.
If you approach this book with a view of getting a *first course in basic statistics*, you will be disappointed and find the book very difficult. Hence many reviewers’ dislike of it. Perhaps the authors are to blame for this, by using the phrase “Introduction to…” in the title, when clearly the book is much more than a mere introduction. To their credit, the authors do warm in the Preface that the book is aimed at beginning graduate students.
So here is the deal: if you are looking for a truly introductory book, try Clarke and Cooke’s “Basic Statistics” or Mendenhall et al.’s “Mathematical Statistics with Applications.” However, if you have some background in basic probability, statistics and calculus, then Hogg et al.’s book will be invaluable to you, because it is extremely well-written (by the very best in the field) and comprehensive. Together with Casella and Berger’s Statistical Inference, it is one of the best existing books in intermediate to advanced statistics.
link
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All Of Nonparametric Statistics
Author(s): Larry Wasserman
Publisher: Springer
Date : 2009
Pages : 284
Format : PDF
OCR :
Quality : Perfect
Language : English
ISBN-10 :
ISBN-13 : 9780387251455
"The goal of this text is to provide readers with a single book where they can find a brief account of many modern topics in nonparametric inference. The book is aimed at master's-level or Ph.D.-level students in statistics, computer science, and engineering. It is also suitable for researchers who want to get up to speed quickly on modern nonparametric methods." This text covers a wide range of topics including the bootstrap, the nonparametric delta method, nonparametric regression, density estimation, orthogonal function methods, minimax estimation, nonparametric confidence sets, and wavelets. The book has a mixture of methods and theory.
link
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Handbook of Parametric and Nonparametric Statistical Procedures
Author(s): David J. Sheskin
Publisher: Taylor & Francis, Inc.
Date : 2007
Pages : 1736
Format : PDF
OCR :
Quality : Perfect
Language : English
ISBN-10 :
ISBN-13 : 9781584888147
Synopsis
In the new edition of this applications-oriented reference work, Sheskin (psychology, Western Connecticut State U.) describes univariate and bivariate statistical procedures used in a wide variety of academic disciplines. Invoking the goal of practicality, he has written the material to be accessible and usable to those who lack the theoretical or mathematical background necessary for understanding convention statistics reference books. Issues of application selection and computational guidelines are discussed. Annotation ©2003 Book News, Inc., Portland, OR
Annotation
Single sample z test, chi-square goodness-of-fit, Wilcoxon signed-ranks test, analysis of variance, etc.
Booknews
A reference on statistical procedures for students and experienced researchers, explaining some 75 parametric and nonparametric procedures with examples relating to experimental design, control, and statistical analysis, emphasizing application over theory. Provides computational guidelines for each procedure, organized in a standardized format using standardized sets of data. Assumes basic familiarity with descriptive statistics and experimental design, although there is an overview provided. Annotation c. by Book News, Inc., Portland, Or.
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