How we did it:
For any feedback, any questions, any notes or just for chat - feel free to follow us on social networks
Jim Gray, Andreas Reuter
A comprehensive presentation of the key concepts and techniques of transaction processing. The authors provide a description of the transaction concepts and how it fits in a distributed computing environment, as well as a thorough discussion of the complex issues related to transaction recovery. The book will be invaluable to anyone interested in using or implementing distributed systems or client server systems.
Robert A. Muenchen
While SAS and SPSS have many things in common, R is very different. My goal in writing this book is to help you translate what you know about SAS or SPSS into a working knowledge of R as quickly and easily as possible. I point out how they differ using terminology with which you are familiar, and show you which add-on packages will provide results most like those from SAS or SPSS. I provide many example programs done in SAS, SPSS, and R so that you can see how they compare topic by topic. When finished, you should be able to use R to: Read data from various types of text files and SAS/SPSS datasets. Manage your data through transformations or recodes, as well as splitting, merging and restructuring data sets. Create publication quality graphs including bar, histogram, pie, line, scatter, regression, box, error bar, and interaction plots. Perform the basic types of analyses to measure strength of association and group differences, and be able to know where to turn to cover much more complex methods.
One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives special attention to possible intertemporal patterns, distributed lag responses of output to input series and the auto correlation patterns of regression disturbance. It also includes six case studies.
Carpenter demystifies the powerful REPORT procedure and shows users how to incorporate this highly flexible and customizable procedure into their SAS reporting programs. Illustrated with over 200 examples and sample exercises to reinforce learning, this resource provides information that can be put to immediate use.
Table of ContentsChapter 1 System overviewChapter 2 ProgrammingChapter 3 General rulesChapter 4 Global statementsChapter 5 Data step statementsChapter 6 Proc step statementsChapter 7 ExpressionsChapter 8 Macro LanguageChapter 9 System optionsChapter 10 FilesChapter 11 Descriptive statisticsChapter 12 Display managerChapter 13 InformatsChapter 14 FormatsChapter 15 FunctionsChapter 16 CALL routinesChapter 17 Base SAS procsChapter 18 Products