Multiple Non-Linear Regression Analysis PDF (Adobe DRM) download by Markus Schief

Multiple Non-Linear Regression Analysis

GRIN Verlag
Publication date: January 2009
ISBN: 9783640237524
Digital Book format: PDF (Adobe DRM)

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Statistical analyses are very important today. In many areas like science or economics, for example, statistical analyses are used to support assumptions and to predict future data. With regards to business administration, modern business statistics can be used to influence decision making in finance, marketing or production, for instance. The scope of the current project is to analyze a data set Ibell of phone calls and to predict future quantity of phone calls based on a regression analysis. The Ibell data set is related to the U.S. based company International Bell Communications (Ibell) that owns and operates direct routes through-out the world (International Bell Communications, 2008). Four variables are provided in the Ibell data set, three independent variables and one dependent (also called response) variable. The independent respectively predictor variables are Quarter, Price (price charged for long-distance calls in US$), and Perinc (reflecting the local average personal income in US$). The dependent variable is Quantity the number of long-distance phone calls. The present data set was provided by the professor of the QMB class. Thus, the data has not been personally collected and hence the author of this report can not personally guarantee for the quality of the data set. However, the predictor variables of Quarter, Price, and Perinc seem fairly reasonable influences on the number of long-distance calls, in general. There are three major parts in this report. First, a general description of the data set will be presented, including the sort of variables, the characteristics of the observations, and the peculiarities in the distribution. Second, regression analyses estimate the validity of a modeled relationship between the dependent and the independent variables. Finally, the researcher will predict future quantity of long-distance calls for the upcoming four quarters in order to support International Bell Communications in network capacity planning as well as in revenue forecasts, for instance. Projektarbeit aus dem Jahr 2008 im Fachbereich Statistik, Note: A, University of West Florida, Sprache: Englisch.
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