Showing all 17 results
Statistik von Null auf Hundert nähert sich der Statistik über Kochrezepte und einfache Beispiele. Der Leser erhält schnell die erforderliche Kompetenzen, um selber Statistiken anfertigen, auch große Zahlenmengen anschaulich zu visualisieren und wesentliche statistische Kennwerte ermitteln zu können. Das schließt die „Statistiklesefähigkeit“ mit ein: Statistische Angaben in Zeitschriften und Büchern werden transparent, auch Manipulationen mit Statistik werden erkannt. Berechnungen und Lösungen von Kombinatorikfragestellungen werden einfach erklärt.
Vast holdings and assessment of consumer data by large companies are not new phenomena. Firms’ ability to leverage the data to reach customers in targeted campaigns and gain market share is, and on an unprecedented scale. Major companies have moved from serving as data or inventory storehouses, suppliers, and exchange mechanisms to monetizing their data and expanding the products they offer. Such changes have implications for both firms and consumers in the coming years.
In Success with Big Data, Russell Walker investigates the use of internal Big Data to stimulate innovations for operational effectiveness, and the ways in which external Big Data is developed for gauging, or even prompting, customer buying decisions.
Risk control, capital allocation, and realistic derivative pricing and hedging are critical concerns for major financial institutions and individual traders alike. Events from the collapse of Lehman Brothers to the Greek sovereign debt crisis demonstrate the urgent and abiding need for statistical tools adequate to measure and anticipate the amplitude of potential swings in the financial markets—from ordinary stock price and interest rate moves, to defaults, to those increasingly frequent “rare events” fashionably called black swan events.
How to make simple sense of complex statistics–from the author of Numbers Rule Your World
We live in a world of Big Data–and it’s getting biggerevery day. Virtually every choice we make hinges on how someone generates data . . . and how someone else interprets it–whether we realize it or not.
Where do you send your child for the best education?Big Data. Which airline should you choose to ensure a timely arrival? Big Data. Who will you vote for in the next election? Big Data.
The problem is, the more data we have, the more difficult it is to interpret it.
Analyzing Event Statistics in Corporate Finance provides new alternative methodologies to increase accuracy when performing statistical tests for event studies within corporate finance. In contrast to conventional surveys or literature reviews, Jeng focuses on various methodological defects or deficiencies that lead to inaccurate empirical results, which ultimately produce bad corporate policies. This work discusses the issues of data collection and structure, the recursive smoothing for systematic components in excess returns, the choices of event windows, different time horizons for the events, and the consequences of applications of different methodologies.
Authors: Madsen, Birger StjernholmAimed at practitionersThe presentation is as non-mathematical as possibleIncludes many examples of the use of statistical functions in spreadsheetsEmploys a realistic sample survey as an exemplar throughout the bookFills a gap in the existing literature on statisticsAbout this TextbookThis book was written for those who need to know how to collect, analyze and present data. It is meant to be a first course for practitioners, a book for private study or brush-up on statistics, and supplementary reading for general statistics classes.
Planning of actions based on decision theory is a hot topic for many disciplines. Seemingly unlimited computing power, networking, integration and collaboration have meanwhile attracted the attention of fields like Machine Learning, Operations Research, Management Science and Computer Science.
STATISTICS FOR BUSINESS AND ECONOMICS brings together more than twenty-five years of author experience, sound statistical methodology, a proven problem-scenario approach, and meaningful applications to demonstrate how statistical information. Discover how the most trusted approach to statistics today is Simply Powerful with the latest market-leading text from respected authors Anderson/Sweeney/Williams. STATISTICS FOR BUSINESS AND ECONOMICS, 11e introduces sound statistical methodology within a strong applications setting.
Apart from a thorough exploration of all the important concepts, this volume includes over 75 algorithms, ready for putting into practice. The book also contains numerous hands-on implementations of selected algorithms to demonstrate applications in realistic settings. Readers are assumed to have a sound understanding of calculus, introductory matrix analysis, and intermediate statistics, but otherwise the book is self-contained. Suitable for graduates and undergraduates in mathematics and engineering, in particular operations research, statistics, and computer science.
Score higher in your business statistics course? Easy.Business statistics is a common course for business majors and MBA candidates. It examines common data sets and the proper way to use such information when conducting research and producing informational reports such as profit and loss statements, customer satisfaction surveys, and peer comparisons."Business Statistics For Dummies" tracks to a typical business statistics course offered at the undergraduate and graduate levels and provides clear, practical explanations of business statistical ideas, techniques, formulas, and calculations, with lots of examples that shows you how these concepts apply to the world of global business and economics.
Handbook of Big Data provides a state-of-the-art overview of the analysis of large-scale datasets. Featuring contributions from well-known experts in statistics and computer science, this handbook presents a carefully curated collection of techniques from both industry and academia. Thus, the text instills a working understanding of key statistical and computing ideas that can be readily applied in research and practice.Offering balanced coverage of methodology, theory, and applications, this handbook:Describes modern, scalable approaches for analyzing increasingly large datasetsDefines the underlying concepts of the available analytical tools and techniquesDetails intercommunity advances in computational statistics and machine learningHandbook of Big Data also identifies areas in need of further development, encouraging greater communication and collaboration between researchers in big data sub-specialties such as genomics, computational biology, and finance.
Among the symmetrical distributions with an infinite domain, the most popular alternative to the normal variant is the logistic distribution as well as the Laplace or the double exponential distribution, which was first introduced in 1774. Occasionally, the Cauchy distribution is also used. Surprisingly, the hyperbolic secant distribution has led a charmed life, although Manoukian and Nadeau had already stated in 1988 that “… the hyperbolic-secant distribution … has not received sufficient attention in the published literature and may be useful for students and practitioners.”
This book is intended for use in a rigorous introductory PhD level course in econometrics, or in a field course in econometric theory. It covers the measure-theoretical foundation of probability theory, the multivariate normal distribution with its application to classical linear regression analysis, various laws of large numbers, central limit theorems and related results for independent random variables as well as for stationary time series, with applications to asymptotic inference of M-estimators, and maximum likelihood theory
Now in its fourth edition, this book offers a detailed yet concise introduction to the growing field of statistical applications in finance. The reader will learn the basic methods of evaluating option contracts, analyzing financial time series, selecting portfolios and managing risks based on realistic assumptions about market behavior. The focus is both on the fundamentals of mathematical finance and financial time series analysis, and on applications to given problems concerning financial markets, thus making the book the ideal basis for lectures, seminars and crash courses on the topic.F
This book covers time series modeling and forecasting for econometrics and finance students. This new edition has been simplified for more ease of use and includes new chapters and substantial important revisions.
Includes lists, tables, and statistics on: Senators Senatorial elections Sessions Party leadership and organization Committees Senate organization and Senate powers.
The aim of this volume is to provide a general overview of the econometrics of panel data, both from a theoretical and from an applied viewpoint. Since the pioneering papers by Kuh (1959), Mundlak (1961), Hoch (1962), and Balestra and Nerlove (1966), the pooling of cross section and time series data has become an increasingly popular way of quantifying economic relationships. Each series provides information lacking in the other, so a combination of both leads to more accurate and reliable results than would be achievable by one type of series alone.
Showing all 17 results