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SPIRES-BOOKS: FIND KEYWORD ELECTRONIC SPREADSHEET *END*INIT* use /tmp/qspiwww.webspi1/9749.7 QRY 131.225.70.96 . find keyword electronic spreadsheet ( in books using www Cover
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Call number:9781118781937:ONLINE Show nearby items on shelf
Title:Excel data analysis: Your visual blueprint for analyzing data, charts, and PivotTables [electronic resource]
Author(s): Paul McFedries
Denise Etheridge
Date:2013
Publisher:New York: Wiley
Size:1 online resource (338 p)
ISBN:9781118781937
Series:EBL eBook
Series:eBooks
Keywords: Microsoft Excel (Computer file). , Business Computer programs. , Electronic spreadsheet.
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Call number:SPRINGER-2014-9781461479000:ONLINE Show nearby items on shelf
Title:XML and Web Technologies for Data Sciences with R [electronic resource]
Author(s): Deborah Nolan
Duncan Temple Lang
Date:2014
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Web technologies are increasingly relevant to scientists working with data, for both accessing data and creating rich dynamic and interactive displays. The XML and JSON data formats are widely used in Web services, regular Webpages and JavaScript cod e, and visualization formats such as SVG and KML for Google Earth and Google Maps. In addition, scientists use HTTP and other network protocols to scrape data from Web pages, access REST and SOAP Web Services,and interact with NoSQL databases and text sea rch applications. This book provides a practical hands-on introduction to these technologies, including high-level functions the authors have developed for data scientists. It describesstrategies and approaches for extracting data from HTML, XML, and JSON formats and how to programmatically access data from the Web. Along with these general skills, the authors illustrate several applications that are relevant todata scientists, such as reading and writing spreadsheet documents both locally and via GoogleD ocs, creating interactive and dynamic visualizations, displaying spatial-temporal displays with Google Earth, and generating code fromdescriptions of data structures to read and write data. These topics demonstrate the rich possibilities and opportunities to do new things with these modern technologies. The book contains many examples and case-studies thatreaders can use directly and adapt to their own work. The authors have focused on the integration of these technologies with the R statistical computing environment. However, the ideas and skills presented here are more general,and statisticians who use other computing environments will also find them relevant to their work. Deborah Nolan is Professor of Statistics at University of California, Berkeley. Duncan Temple Lang is Associate Professor of Statisticsat University of California, Davis and has been a member of both the S and R development teams
Contents:Data Formats XML and JSON
Web Technologies, Getting Data from the Web
General XML Application Areas
Bibliography
General Index
R Function and Parameter Index
R Package Index
R Class Index
Colophon
ISBN:9781461479000
Series:eBooks
Series:SpringerLink
Series:Use R!, 2197-5736
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Computer science , Mathematical statistics
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Call number:SPRINGER-2012-9780387779072:ONLINE Show nearby items on shelf
Title:Visualizing Time [electronic resource] : Designing Graphical Representations for Statistical Data
Author(s): Graham Wills
Date:2012
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Art, or Science? Which of these is the right way to think of the field of visualization? This is not an easy question to answer, even for those who have many years experience in making graphical depictions of data with a view tohelp people understand it and take action. In this book, Graham Wills bridges the gap between the art and the science of visually representing statistical data. He does not simply give rules and advice, but bases these on generalprinciples and provides a clear path between the m. This book is concerned with the graphical representation of time data and is written to cover a range of different users. A visualization expert designing tools for displaying timewill find it valuable, but so also should a financier assembling a repo rt in a spreadsheet, or a medical researcher trying to display gene sequences using a commercial statistical package
Note:Springer eBooks
Contents:History
Framework
Designing Visualizations
Types of Data
Time as a Coordinate
Coordinate Systems, Transformations, Faceting, and Axes
Aesthetics
Transformations
Interactivity
Topics in Time
Gallery of Figures
ISBN:9780387779072
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics and Computing, 1431-8784
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Mathematical statistics
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Call number:SPRINGER-2010-9781441913142:ONLINE Show nearby items on shelf
Title:Between Theory and Observations [electronic resource] : Tobias Mayer's Explorations of Lunar Motion, 1751-1755
Author(s): Steven Wepster
Date:2010
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:In the 18th century purely scientific interests as well as the practical necessities of navigation motivated the development of new theories and techniques to accurately describe celestial and lunar motion. Tobias Mayer, a Germanmathematician and ast ronomer, was among the most notable scientists of the time in the area of lunar theory. Between Theory and Observations presents a detailed and rigorous account of Tobias Mayers work his famous contributionis his extensive set of lunar tables, which were the most accurate of their time. This book gives a complete and accurate account, not to be found elsewhere in the literature, of Tobias Mayer's important contributions to the study oflunar motion. The book highlights and examines three of Mayer's major a chievements: - The computational scheme embodied in Mayer's lunar tables is examined and traced back to the scheme of Newton's 1702 lunar theory with its decidedlynon-dynamical characteristics. - Mayer's dynamical lunar theory is compared to Euler's work in celestial mechanics of the same period. Evidence is presented refuting the commonly held opinion that Mayer's lunar theory was simply amodification of Euler's theory. - Mayer's technique of adjusting the coefficients of his lunar tables to fit an exten sive collection of observational data is examined in detail. The scale of Mayer's effort was unprecedented andpreceded the invention of the least squares method by half a century. This volume is intended for historians of mathematics and/or astronomy as w ell as anyone interested in the historical development of the theory of lunar motion
Note:Springer eBooks
Contents:List of Figures. List of Displays
1. Introduction
2. The quest for lunar theory
3. The poineer's work
4. A manual to the tables
5. Theoria Lunae
6. The Horrocks legacy
7. Multisteps in the Theoria Lunae
8. Hausbackene Combinationen
9. Some aspects of model fitting
10. Concluding observations
Appendix A. Lunar equations: versions and aliases
Appendix B. Spreadsheet contents
Appendix C. Manuscript sources
References
Index
ISBN:9781441913142
Series:e-books
Series:SpringerLink (Online service)
Series:Sources and Studies in the History of Mathematics and Physical Sciences
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Mathematics_$xHistory , Astronomy
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Call number:SPRINGER-2009-9781441900524:ONLINE Show nearby items on shelf
Title:R Through Excel [electronic resource] : A Spreadsheet Interface for Statistics, Data Analysis, and Graphics
Author(s): Richard M Heiberger
Erich Neuwirth
Date:2009
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:R, a free and open source program, is one of the most powerful and the fastest-growing statistics program. Microsoft Excel is the most widely used spreadsheet program, but many statisticians consider its statistical tools toolimited. In this book, th e authors build on RExcel, a free add-in for Excel that can be downloaded from the R distribution network. RExcel seamlessly integrates the entire set of R's statistical and graphical methods into Excel,allowing students to focus on statistical methods an d concepts and minimizing the distraction of learning a new programming language. Data can be transferred between R and Excel the Excel way by selecting worksheet ranges and usingExcel menus. R's basic statistical functions and selected advanced methods a re available from an Excel menu. Results of the computations and statistical graphics can be returned back into Excel worksheet ranges. RExcel allows the useof Excel scroll bars and check boxes to create and animate R graphics as an interactive analysis t ool. The book is designed as a computational supplement to introductory statistics texts and the authors provide RExcel examples coveringthe topics of the introductory course. Richard M. Heiberger is Professor of Statistics at Temple University. He partic ipated in the design of the S-Plus and R linear model and analysis of variance functions while on research leave atBell Labs. He is the author of and contributor to various R packages. He is an Elected Fellow of the American Statistical Association (ASA) and the Chair Elect of the ASA Section on Statistical Computing. Erich Neuwirth is Professor ofComputer Science at the University of Vienna and was formerly Professor of Statistics. He is the author of RExcel, and author of and contributor to various R pa ckages. He is coauthor of Mathematical Modeling with Excel, winner of theEuropean Academic Software Award 1996 (for a project combining mathematics and music), and Associate Editor for Computational S
Note:Springer eBooks
Contents:Getting Started
Using RExcel and R Commander
Getting Data into R
Normal and Distributions
Normal and Workbook
Tests
One
Way ANOVA
Simple Linear Regression
What Is Least Squares?
Multiple RegressionTwo
Variables
Polynomial Regression
Multiple RegressionThree or More
Variables
Contingency Tables and the Chi
Square Test
ISBN:9781441900524
Series:e-books
Series:SpringerLink (Online service)
Series:Use R
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Mathematical statistics
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Call number:SPRINGER-2009-9780387879598:ONLINE Show nearby items on shelf
Title:Applying Quantitative Bias Analysis to Epidemiologic Data [electronic resource]
Author(s): Timothy L Lash
Matthew P Fox
Aliza K Fink
Date:2009
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This text provides the first-ever compilation of bias analysis methods for use with epidemiologic data. It guides the reader through the planning stages of bias analysis, including the design of validation studies and thecollection of validity data f rom other sources. Three chapters present methods for corrections to address selection bias, uncontrolled confounding, and classification errors. Subsequent chapters extend these methods to multidimensionalbias analysis, probabilistic bias analysis, and m ultiple bias analysis. The text concludes with a chapter on presentation and interpretation of bias analysis results. Although techniques for bias analysis have been available fordecades, these methods are considered difficult to implement. This text not only gathers the methods into one cohesive and organized presentation, it also explains the methods in a consistent fashion and provides customizablespreadsheets to implement the solutions. By downloading the spreadsheets (available at links provided in t he text), readers can follow the examples in the text and then modify the spreadsheet to complete their own bias analyses.Readers without experience using quantitative bias analysis will be able to design, implement, and understand bias analyses that addr ess the major threats to the validity of epidemiologic research. More experienced analysts will valuethe compilation of bias analysis methods and links to software tools that facilitate their projects. Timothy L. Lash is an Associate Professor of Epidemio logy and Matthew P. Fox is an Assistant Professor in the Center for InternationalHealth and Development, both at the Boston University School of Public Health. Aliza K. Fink is a Project Manager at Macro International in Bethesda, Maryland. Together they have organized and presented many day-long workshops on themethods of quantitative bias analysis. In addition, they have collaborated on many papers that developed methods of quantitative bias analysis
Note:Springer eBooks
Contents:Introduction, objectives and an alternative
A guide to implementing quantitative bias analysis
Data sources for bias analysis
Selection bias
Unmeasured and unknown confounders
Misclassification
Multidimensional bias analysis
Probabilistic bias analysis
Multiple bias modeling
Presentation and inference
ISBN:9780387879598
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Biology and Health, 1431-8776
Series:Mathematics and Statistics (Springer-11649)
Keywords: Medicine , Emerging infectious diseases , Epidemiology , Computer simulation , Statistics , Social sciences Methodology
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Call number:SPRINGER-2006-9780387316079:ONLINE Show nearby items on shelf
Title:Binomial Models in Finance [electronic resource]
Author(s): John Hoek
Robert J Elliott
Date:2006
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This book deals with many topics in modern financial mathematics in a way that does not use advanced mathematical tools and shows how these models can be numerically implemented in a practical way. The book is aimed atundergraduate students, MBA stud ents, and executives who wish to understand and apply financial models in the spreadsheet computing environment. The basic building block is the one-step binomial model where a known price today can takeone of two possible values at the next time. In this simple situation, risk neutral pricing can be defined and the model can be applied to price forward contracts, exchange rate contracts, and interest rate derivatives. The simpleone-period framework can then be extended to multi-period models. The authors show how binomial tree models can be constructed for several applications to bring about valuations consistent with market prices. The book closes with anovel discussion of real options. John van der Hoek is Senior Lecturer in Applied Mathematics at the University of Adelaide. He has developed courses in finance for a number of years at various levels and is a regular plenary speakerat major conferences on Quantitative Finance. Robert J. Elliott is RBC Financial Group Professor of Finance at the Haskayne School of Business at the University of Calgary. He is the author of over 300 research papers and severalbooks, including Mathematics of Financial Markets, Second Edition (with P. Ekkehard Kopp), Stochastic Calculus and Applications, Hidden Markov Models (with Lahkdar Aggoun and John Moore) and Measure Theory and Filtering: Theory andApplications (with Lakhdar Aggoun). He is an Associate Editor of Mathematical Finance, Stochastics and Stochastics Reports, Stochastic Analysis and Applications, and the Can adian Applied Mathematics Quarterly
Note:Springer eBooks
Contents:Introduction
The binomial model for stock options
The binomial model for other contracts
Multiperiod binomial models
Hedging
Forward and futures contracts
American and exotic option pricing
Path dependent options
The Greeks
Dividends
Implied volatility trees
Implied binomial trees
Interest rate models
Real options
The binomial distribution
An application of linear programming
Volatility estimation
Existence of a solution
Some generalizations
Yield curves and splines
ISBN:9780387316079
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Finance
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Finance , Economics Statistics , Economics, Mathematical
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