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Multiple regression: chapter 9

dc.contributor.authorMakridakis, Spyros
dc.contributor.authorWheelright, Steven
dc.date.accessioned2015-12-16T14:53:15Z
dc.date.available2015-12-16T14:53:15Z
dc.date.issued1989
dc.identifier.isbn978-0471600633
dc.identifier.urihttp://hdl.handle.net/11728/6670
dc.description.abstractIn Chapter 8 simple regression and correlation were introduced and discussed. In simple regression the basic proposition is that an independent variable can be used to predict the value of some dependent variable (the quantity to be forecast) on the basis of a linear relationship between the two variables. In the major example in that chapter the variable to be forecast was the number of orders received daily by a mail-order house. The independent variable on which that forecast was based was the weight of all mail for that day. In many decision-making situations more than one variable can be used to explain or forecast a certain dependent variable. For example, in the mail-order situation the day of the week, as weil as the weight of mail received, might be used to predict the number of orders.en_UK
dc.language.isoenen_UK
dc.publisherWiley, John & Sonsen_UK
dc.rights© 1989, Wiley, John & Sonsen_UK
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_UK
dc.subjectEconomic forecastingen_UK
dc.subjectmethodologyen_UK
dc.subjectBusiness forecastingen_UK
dc.titleMultiple regression: chapter 9en_UK
dc.title.alternativeForecasting Methods for Management 5th Editionen_UK
dc.typeBook chapteren_UK


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© 1989, Wiley, John & Sons
Except where otherwise noted, this item's license is described as © 1989, Wiley, John & Sons