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SPSS for Intermediate Statistics: Use and Interpretation




SPSS for Intermediate Statistics: Use and Interpretation
Publisher: Lawrence Erlbaum | ISBN: 0805847901 | edition 2004 | PDF | 255 pages | 16,18 mb

This book is designed to help students learn to analyze and interpret research data using intermediate statistics. The new edition features SPSS 12.0 for Windows, but can also be used with versions 10 and 11. Each chapter introduces several related statistics and provides instructions on how to run them and interpret the outputs. The authors describe the use and interpretation of these statistics in user-friendly, non-technical, jargon-free language. The examples use realistic data available on the CD in the back of the book. The authors' goal is to demonstrate: how to choose the appropriate statistic based on the research design, how to use SPSS to answer research questions, how to interpret SPSS outputs, and how to write about the outputs in the results section of a research paper.

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Probability: An Introduction




Geoffrey Grimmett, Dominic Welsh, "Probability: An Introduction"
Oxford University Press, USA | 1986 | ISBN: 0198532725 | 210 pages | Djvu | 1,3 MB

This new undergraduate text offers a concise introduction to probability and random processes. Exercises and problems range from simple to difficult, and the overall treatment, though elementary, includes rigorous mathematical arguments. Chapters contain core material for a beginning course in probability, a treatment of joint distributions leading to accounts of moment-generating functions, the law of large numbers and the central limit theorem, and basic random processes.


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Probabilities on Algebraic Structures (Dover Books on Mathematics)



Probabilities on Algebraic Structures (Dover Books on Mathematics) By Ulf Grenander
Publisher: Dover Publications 2008-02-04 | 224 Pages | ISBN: 0486462870 | PDF | 1 MB
A systematic account of the theory of probability for certain sample spaces with algebraic structure, this text covers semi-groups, groups, linear vector spaces, and algebra. It states and studies fundamental probabilistic problems for these spaces, focusing on concrete results rather than on general and complete answers. 1963 edition.



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Intuitive Probability and Random Processes using MATLAB: Steven Kay



Intuitive Probability and Random Processes using MATLAB: Steven Kay
Springer | ISBN: 0387241574 | 2005-11-16 | PDF (OCR) | 833 pages | 51.3 Mb

Intuitive Probability and Random Processes using MATLAB is an introduction to probability and random processes that merges theory with practice. Based on the author's belief that only "hands-on" experience with the material can promote intuitive understanding, the approach is to motivate the need for theory using MATLAB examples, followed by theory and analysis, and finally descriptions of "real-world" examples to acquaint the reader with a wide variety of applications. The latter is intended to answer the usual question "Why do we have to study this?" Other salient features are: *heavy reliance on computer simulation for illustration and student exercises *the incorporation of MATLAB programs and code segments *discussion of discrete random variables followed by continuous random variables to minimize confusion *summary sections at the beginning of each chapter *in-line equation explanations *warnings on common errors and pitfalls *over 750 problems designed to help the reader assimilate and extend the concepts Intuitive Probability and Random Processes using MATLAB is intended for undergraduate and first-year graduate students in engineering. The practicing engineer as well as others having the appropriate mathematical background will also benefit from this book. About the Author Steven M. Kay is a Professor of Electrical Engineering at the University of Rhode Island and a leading expert in signal processing. He has received the Education Award "for outstanding contributions in education and in writing scholarly books and texts..." from the IEEE Signal Processing society and has been listed as among the 250 most cited researchers in the world in engineering.
Summary: More bang for your buck
Rating: 4
Here's what you need to know about this book: 1. Don't be confused about the title. By "intuitive" he means he's not going into theoretical measure theory stuff. The material here is standard material, found on many books.
2. The explanations are very clear, doesn't hold back on formalism (to the extent it's possible to be formal - meaning, he's not sloppy about his presentation), and are followed or preceded by real world examples.
3. You get to use Matlab. That is, you learn the basics of using a computer for problems that are aproximate to real world problems.
4. But just because he uses Matlab doesn't mean you don't have a lot (a lot) of traditional excercises. The computer learning is not necessary, it's a "bonus".
5. This book has over 800 pages, and has many illustrations that help a lot in understanding!
6. Later chapters go into more advanced stuff you probably won't see in your first course in probability.
So, all in all, this is an excellent purchase. The author is very talented in explaining, chooses very good examples and additionally, you get to put this stuff your learning to practice using a computer. I think all these factors make the book stand out and introduce probability in a modern way. If you're having difficulty with other shorter texts (as I was) and if you've got an itch to scratch (wants to use your computer to simulate some stuff and do some problems), I think you'll enjoy and benefit quite a lot from this book. Maybe some other books are a little more demanding on math (e.g. Ross), but it's no use if you cant' understand or if you want to become more proficient in the use of the computer for the modelling of probability problems. The real world problems will appeal more to engineering/applied math/comp sci students than other (e.g., biology students).
The criticism I have is that I would have prefered if it had used the free/open source R language/environment (but I guess since the author comes from Electrical Engineering, Matlab makes more sense). Also, I would like to have a solutions manual for *all* the exercises that's not only for teachers (this American infantile treatment of students bothers me). I would have liked more "mathy" examples such as those Ross has ("harder" examples).
Summary: Pretty good book, worth buying
Rating: 4
This is a good book, I have been reading it, so far I enjoy it. compared with other book on the same topic, this book is worth buying.
Summary: Very pedagogical exposition
Rating: 4
you will get a solid understanding of each topic/chapter title. Not only engineering but also math students should be trained in the spirit of this book. Each chapter culminates in a real world application which is indeed interesting, and not completely trivial. Few books teach the theory but also bring you to the level where you can apply this theory to problems. However, there is a drawback, in my opinion; since the book is supposed to address grad students some mathematical sophistication could be assumed so as to achieve a more concise presentation. I don't blame the author for extreme clarity of course, but usually you want to get to the interesting parts of any subject at a much higher pace. At some points one could say the book is a bit verbose. Overall, it is almost excellent taking into account its target-group (mostly ece students) and the material it deals with (elementary applied probability).
Summary: Excellent Book
Rating: 5
This is a very good book for classes and suitable for textbook. I recomend this book for who is the new in the probability. The book is readable, clear explaination and MATLAB examples are understandable.
N.A.S.
Summary: Intuitive as it says
Rating: 5
It's a great book for probability. Explain the abstract concept in an easy way. You will find out that you go through all those difficulties just by following the author. I got full point in my first quiz which was never the case for my math courses.

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Even You Can Learn Statistics
A Guide for Everyone Who Has Ever Been Afraid of Statistics
Author(s): David M. Levine, David F. Stephan
Publisher: FT Press
Size:-3.5MB
Date : 2009
Pages : 384
Format : PDF
OCR : yes
Language : English
ISBN-10 : 0137010591


Description
Even You Can Learn Statistics, 2nd Ed. is the easiest guide to using statistics in your everyday work or study. Experienced educators David Levine and David Stephan teach statistics hands-on, in plain English, with as little math and as many revealing examples as possible. Levine and Stephan define each concept and technique in plain English, and then explain why it's important, when it's used, and how you can apply it yourself. This Second Edition is fully-updated with new examples that designed to be easily worked with Microsoft Excel, the free OpenOffice.org Calc spreadsheet program, or any TI-83 compatible calculator. This new edition also adds detailed problems and worked solutions at the end of every chapter, along with a library of updated multiple choice questions that help you quickly test and build your knowledge. It contains more Excel and OpenOffice.org guidance, as well as an entirely new chapter on multiple regression, the powerful statistical tool for understanding the relationship between several independent variables in applications ranging from business to science. If you do want to understand statistics' deeper mathematical foundations, optional "Equation Blackboard" sections illuminate the equations at work beneath many of today's most crucial statistical techniques. Along the way, Levine and Stephan also help you overcome common misconceptions about statistics, so you can use any statistical method more confidently and successfully.

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[albertnammas]

Mathematical Statistics
Unified Introduction
Author(s): George R. Terrell
Publisher: Springer
Date : 1999
Pages : 453
Format : PDF
Size:-1.96Mb
Language : English
ISBN-10 : 0387986219

Description
This textbook introduces the mathematical concepts and methods that underlie statistics. The course is unified, in the sense that no prior knowledge of probability theory is assumed; this is developed as needed. The book is committed to a high level of mathematical seriousness; and to an intimate connection with application. Modern methods, such as logistic regression, are introduced; as are unjustly neglected clasical topics, such as elementary asymptotics. The book first develops elementary linear models for measured data and multiplicative models for counted data. Simple probability models for random error follow. The most important famiies of random variables are then studied in detail, emphasizing their interrelationships and their large-sample behavior. Inference, including classical, Bayesian, finite population, and likelihood-based, is introduced as the necessary mathematical tools become available. In teaching style, the book aims to be * mathematically complete: every formula is derived, every theorem proved at the appropriate level * concrete: each new concept is introduced and exemplified by interesting statistical problems; and more abstract concepts appear only gradually * constructive: direct derivations and proofs are preferred * active: students are led to do mathematical statistics, not just to appreciate it, with the assistance of 500 interesting exercises. The text is aimed for the upper undergraduate level, or the beginning Masters program level. It assumes the usual two-year college mathematics sequence, including an introduction to multiple integrals, matrix algebra, and infinite series.

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Basic Statistics
Understanding Conventional Methods and Modern Insights
Author(s): Rand R. Wilcox
Publisher: Oxford University Press
Size:-1.22MB
Date : 2009
Pages : 344
Format : PDF
OCR : Yes
Language : English
ISBN-10 : 0195315103

Description
This introductory statistics textbook for non-statisticians covers basic principles, concepts, and methods routinely used in applied research. What sets this text apart is the incorporation of the many advances and insights from the last half century when explaining basic principles. These advances provide a foundation for vastly improving our ability to detect and describe differences among groups and associations among variables and provide a deeper and more accurate sense of when basic methods perform well and when they fail. Assuming no prior training, Wilcox introduces students to basic principles and concepts in a simple manner that makes these advances and insights, as well as standard ideas and methods, easy to understand and appreciate.

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[ابن الخطاب]

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P 40 Puzzles and Problems in Probability and Mathematical Statistics



Wolfgang Schwarz, "40 Puzzles and Problems in Probability and Mathematical Statistics"
Springer 2007 | ISBN-10: 0387735119 | 124 pages | PDF | 2,2 MB

The present book is based on the view that cognitive skills are best acquired by solving challenging, non-standard probability problems. The author's own experience, both in learning and in teaching, is that challenging problems often provide more, and longer lasting, inductive insights than plain-style deductions from general concepts. Problems help to develop, and to sharpen our intuition for important probabilistical concepts and tools such as conditionaing or first-step analyses.
Many puzzles and problems presented here are either new within a problem solving context (although as topics in fundamental research they are of course long known) or are variations of classical problems which follow directly from elementary concepts. A small number of particularly instructive problems is taken from previous sources which in this case are generally given.

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Probability Theory, an Analytic View



Publisher: Cambridge University | Pages: 536 | 2000-01-28 | ISBN 0521663490 | PDF | 3 MB
This revised edition of Daniel W. Stroock's classic text is suitable for a first-year graduate course on probability theory. By modern standards the topics treated are classical and the techniques used far-ranging: Dr. Stroock does not approach the subject as a monolithic structure resting on a few basic principles. The first part of the book deals with independent random variables, Central Limit phenomena, the general theory of weak convergence and several of its applications, as well as elements of both the Gaussian and Markovian theory of measures on function space. Stroock covers conditional expectation values in the second half where he applies them to the study of martingales. He also explores the connection between martingales and various aspects of classical analysis and the connections between Wiener's measure and classical potential theory. Student prerequisites are a good grasp of introductory, undergraduate probability theory and a reasonably sophisticated knowledge of analysis.




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Data Distributions




Data Distributions
Publisher: Pearson Prentice Hall | pages: 103 | 2006 | ISBN: 0131656465 | PDF | 11,2 mb

Four investigations focus students’ attention on distributions of data, variability, measure of center, and comparing data sets.
Students will learn to choose among a variety of representations to display distributions and will analyze, describe, and compare sets of data.

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