AMECO is the annual macro-economic database of the European Commission's Directorate General for Economic and Financial Affairs. The database is used for analysis and reports produced by the directorate general.
ALFRED® allows you to retrieve vintage versions of economic data that were available on specific dates in history. In general, economic data for past observation periods are revised as more accurate estimates become available.
International financial reports provide statistics, analysis, reports, surveys and breaking news on industries, countries and consumers worldwide.
Also connects market research to your company goals and annual planning, analyzing market context, competitor insight and future trends impacting businesses globally.
The mission of the SEC is to protect investors; maintain fair, orderly, and efficient markets; and facilitate capital formation. The SEC strives to promote a market environment that is worthy of the public's trust.
Source for international business and trade information on all 50 U.S. states. In addition to demographic, economic, and historical information on each state, you will find data on corporations with headquarters in each state, and links to state-specific resources.
The IMF publishes a range of time series data on IMF lending, exchange rates and other economic and financial indicators. Manuals, guides, and other material on statistical practices at the IMF, in member countries, and of the statistical community at large are also available.
The NBER data collection here is an eclectic mix of public use economic, demographic, and enterprise data obtained over the years to satisfy the specific requests of NBER affiliated researchers for particular projects.
Applied Statistics with SPSS by Eelko HuizinghAccessibly written and easy to use, Applied Statistics Using SPSS is an all-in-one self-study guide to SPSS and do-it-yourself guide to statistics. What is unique about Eelko Huizingh's approach is that this book is based around the needs of undergraduate students embarking on their own research project, and its self-help style is designed to boost the skills and confidence of those that will need to use SPSS in the course of their research project. The book is pedagogically well developed and contains many screen dumps and exercises, glossary terms, and worked examples. Divided into three parts, Applied Statistics Using SPSS covers: A self-study guide for learning how to use SPSS A reference guide for selecting the appropriate statistical technique A stepwise do-it-your-self guide for analyzing data and interpreting the results Geared explicitly for undergraduate needs, this is an easy to follow SPSS book that should provide a step-by-step guide to research design and data analysis using SPSS.
Call Number: Main 2nd Floor: QA276.4 .H82 2007
ISBN: 9781412919302
Publication Date: 2007-02-28
Statistical Thinking in Business by D. Whitaker; J. A. John; D.G. JohnsonBusiness students need the ability to think statistically about how to deal with uncertainty and its effect on decision-making in business and management. Traditional statistics courses and textbooks tend to focus on probability, mathematical detail, and heavy computation, and thus fail to meet the needs of future managers. Statistical Thinking in Business, Second Edition responds to the growing recognition that we must change the way business statistics is taught. It shows how statistics is important in all aspects of business and equips students with the skills they need to make sensible use of data and other information. The authors take an interactive, scenario-based approach and use almost no mathematical formulas, opting to use Excel for the technical work. This allows them to focus on using statistics to aid decision-making rather than how to perform routine calculations. New in the Second Edition A completely revised chapter on forecasting Re-arrangement of the material on data presentation with the inclusion of histograms and cumulative line plots A more thorough discussion of the analysis of attribute data Coverage of variable selection and model building in multiple regression End-of-chapter summaries More end-of-chapter problems A variety of case studies throughout the book The second edition also comes with a wealth of ancillary materials provided on a CD-ROM packaged with the book. These include automatically-marked multiple-choice questions, answers to questions in the text, data sets, Excel experiments and demonstrations, an introduction to Excel, and the StiBstat Add-In for stem and leaf plots, box plots, distribution plots, control charts and summary statistics.
Call Number: Main 2nd Floor- QA276.12 .J375 2006
ISBN: 9781584884958
Publication Date: 2005-08-29
Data Mining and Business Analytics with R by Johannes LedolterCollecting, analyzing, and extracting valuable information froma large amount of data requires easily accessible, robust,computational and analytical tools. Data Mining and BusinessAnalytics with R utilizes the open source software R for theanalysis, exploration, and simplification of large high-dimensionaldata sets. As a result, readers are provided with the neededguidance to model and interpret complicated data and become adeptat building powerful models for prediction and classification. Highlighting both underlying concepts and practicalcomputational skills, Data Mining and Business Analytics withR begins with coverage of standard linear regression and theimportance of parsimony in statistical modeling. The book includesimportant topics such as penalty-based variable selection (LASSO);logistic regression; regression and classification trees;clustering; principal components and partial least squares; and theanalysis of text and network data. In addition, the bookpresents: ? A thorough discussion and extensive demonstration of thetheory behind the most useful data mining tools ? Illustrations of how to use the outlined concepts inreal-world situations ? Readily available additional data sets and related Rcode allowing readers to apply their own analyses to the discussedmaterials ? Numerous exercises to help readers with computing skillsand deepen their understanding of the material Data Mining and Business Analytics with R is an excellentgraduate-level textbook for courses on data mining and businessanalytics. The book is also a valuable reference for practitionerswho collect and analyze data in the fields of finance, operationsmanagement, marketing, and the information sciences.
Call Number: Main 2nd Floor - QA76.9.D343 L44 2013
ISBN: 9781118447147
Publication Date: 2013-05-28
Statistical Techniques for Forensic Accounting: understanding the theory and application of data analysis by Saurav K. DuttaFraud or misrepresentation often creates patterns of error within complex financial data. The discipline of statistics has developed sophisticated techniques and well-accepted tools for uncovering these patterns and demonstrating that they are the result of deliberate malfeasance. Statistical Techniques for Forensic Accounting is the first comprehensive guide to these tools and techniques: understanding their mathematical underpinnings, using them properly, and effectively communicating findings to non-experts. Dr. Saurav Dutta, one of the field's leading experts, has been engaged as an expert in many of the world's highest-profile fraud cases, including Worldcom, Global Crossing, Cendant, and HealthSouth. Now, he covers everything forensic accountants, auditors, investigators, and litigators need to know to use these tools and interpret others' use of them. Coverage includes: Exploratory data analysis: identifying the "Fraud Triangle" and other red flags Data mining: tools, usage, and limitations Traditional statistical terms and methods applicable to forensic accounting Uncertainty and probability theories and their forensic implications Bayesian analysis and networks Statistical inference, sampling, sample size, estimation, regression, correlation, classification, and prediction How to construct and conduct valid and defensible statistical tests How to articulate and effectively communicate findings to other interested and knowledgeable parties