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The 4th edition demonstrates how a wide variety of statistical analyses, including descriptive statistics, graphics, and model estimation and diagnostics, can be performed using Stata version 9. The authors present many of Stata's novel features, including a new mixed-models estimation command and a new matrix language. This ed. also contains additional exercises that use various data sets and numerous examples of real-life data, enabling a better understanding of the methodology. The book offers selected solutions in an appendix.

#SBIB:303H4 --- #SBIB:303H520 --- Mathematical statistics --- -519.50285 --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Informatica in de sociale wetenschappen --- Methoden sociale wetenschappen: techniek van de analyse, algemeen --- Data processing --- Statistical methods --- Data processing. --- 519.50285 --- Stata.

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Mathematical statistics --- Data processing --- Data processing. --- MATLAB. --- -519.50285 --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Statistical methods --- MATLAB (Computer program) --- Matrix laboratory --- Mathematical statistics - Data processing

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Getting started with SAS is easy with The Little SAS Book. This friendly, easy-to-read guide gently introduces you to the most commonly used features of SAS software plus a whole lot more! The book has been revised to include concepts of the Output Delivery System; the STYLE= option in the PRINT, REPORT, and TABULATE procedures; ODS HTML, RTF, PRINTER, and OUTPUT destinations; PROC REPORT; more on PROC TABULATE; exporting data; and the colon modifier for informats. You'll find clear and concise explanations of basic SAS concepts (such as DATA and PROC steps), inputting data, modifying and combining data sets, summarizing and presenting data, basic statistical procedures, and debugging SAS programs. Each topic is presented in a self-contained, two-page layout complete with examples and graphics. This format enables new users to get up and running quickly, while the examples allow you to type in the program and see it work!

QA 76.755 - Computer Software. Handbook --- SAS --- Mathematical statistics --- Data processing. --- -519.50285 --- 005.5 --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Data processing --- Statistical methods --- SAS (Computer file) --- Statistical analysis system --- SAS system --- 681.3*G --- 681.3*G Mathematics of computing --- Mathematics of computing --- Programming

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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 Holland has 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.

Mathematical statistics --- Statistics --- R (Computer program language) --- Data processing --- S-Plus --- SAS (Computer file) --- regressie-analyse --- tijdreeksanalyse --- wiskundige statistiek --- 519.2 --- -Statistics --- -R (Computer program language) --- 519.50285 --- GNU-S (Computer program language) --- Domain-specific programming languages --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Statistical inference --- Statistics, Mathematical --- Probabilities --- Sampling (Statistics) --- Probability. Mathematical statistics --- S-Plus. --- Statistical analysis system --- SAS system --- SPlus --- 519.2 Probability. Mathematical statistics --- Probabilities. --- Statistics . --- Probability Theory and Stochastic Processes. --- Statistical Theory and Methods. --- Probability --- Combinations --- Chance --- Least squares --- Risk --- Mathematical statistics - Data processing --- Statistics - Data processing

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This is the first book on applied econometrics using the R system for statistical computing and graphics. It presents hands-on examples for a wide range of econometric models, from classical linear regression models for cross-section, time series or panel data and the common non-linear models of microeconometrics such as logit, probit and tobit models, to recent semiparametric extensions. In addition, it provides a chapter on programming, including simulations, optimization, and an introduction to R tools enabling reproducible econometric research. An R package accompanying this book, AER, is available from the Comprehensive R Archive Network (CRAN) at http://CRAN.R-project.org/package=AER. It contains some 100 data sets taken from a wide variety of sources, the full source code for all examples used in the text plus further worked examples, e.g., from popular textbooks. The data sets are suitable for illustrating, among other things, the fitting of wage equations, growth regressions, hedonic regressions, dynamic regressions and time series models as well as models of labor force participation or the demand for health care. The goal of this book is to provide a guide to R for users with a background in economics or the social sciences. Readers are assumed to have a background in basic statistics and econometrics at the undergraduate level. A large number of examples should make the book of interest to graduate students, researchers and practitioners alike. Christian Kleiber is Professor of Econometrics and Statistics at Universität Basel, Switzerland. Achim Zeileis is Assistant Professor in the Dept. of Statistics and Mathematics at Wirtschaftsuniversität Wien, Austria. R users since version 0.64.0, they have been collaborating on econometric methodology in R, including several R packages, for the past eight years. .

Economics/Management Science. --- Econometrics. --- Statistics for Business/Economics/Mathematical Finance/Insurance. --- Game Theory/Mathematical Methods. --- Quantitative Finance. --- Game Theory, Economics, Social and Behav. Sciences. --- Economics. --- Mathematics. --- Finance. --- Economics --- Economics, Mathematical. --- Economie politique --- Mathématiques --- Finances --- Econométrie --- Mathématiques économiques --- Statistics. --- R (Computer program language) --- Econometrics --- Statistics --- Data processing --- Econometrics -- Data processing. --- R (Computer program language). --- Statistics -- Data processing. --- Mathematics --- Mathematical Statistics --- Physical Sciences & Mathematics --- -Econometrics --- -Statistics --- -519.50285 --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Economics, Mathematical --- GNU-S (Computer program language) --- Domain-specific programming languages --- Electronic information resources --- -Electronic information resources --- E-books --- AA / International- internationaal --- 305.971 --- 330.115 --- Speciale gevallen in econometrische modelbouw. --- Econometrie --- 330.115 Econometrie --- Data processing. --- Economic theory. --- Economic Theory/Quantitative Economics/Mathematical Methods. --- Speciale gevallen in econometrische modelbouw --- Statistics for Business, Management, Economics, Finance, Insurance. --- Math --- Science --- Funding --- Funds --- Currency question --- Economic theory --- Political economy --- Social sciences --- Economic man --- Statistics . --- Economics, Mathematical . --- Game theory. --- Games, Theory of --- Theory of games --- Mathematical models --- Mathematical economics --- Methodology --- Econometrics - Data processing --- Statistics - Data processing