Curso de econometria aplicada online dating
PPT – TOPICOS DE ECONOMETRIA APLICADA Series de Tiempo Introducci Power Point presentation | free to download - id: 28c470-NGRm ZThe Adobe Flash plugin is needed to view this content Get the plugin now 14(No Transcript) 15(No Transcript) 165.Proceso estocástico de raíz unitaria Si rho es igual a uno se convierte en un random walk Problema de raíz unitaria (no estacionariedad) Si el valor absoluto de rho es menor a uno la serie es estacionaria Es un AR(1) Los procesos AR(1) son estacionarios 17Procesos de tendencia estacionaria y de diferencia estacionaria Power is a leading presentation/slideshow sharing website.And while it is important to know and understand these tools, here, I want to go at it from a different angle: What is the task at hand that data science tools can help tackle, and what question do we want to have answered?A straight-forward business problem is to estimate future sales and future income. data from past sales, data science can help improve forecasts and generate models that describe the main factors of influence.This, in turn, can then be used to develop actions based on what we have learned, like where to increase advertisement, how much of which products to keep in stock, etc.
Or use it to find and download high-quality how-to Power Point ppt presentations with illustrated or animated slides that will teach you how to do something new, also for free.Because the number of returns is much smaller than the number of purchases, it is difficult to visualize and compare them in the same plot.While above, I split them into two facets with free scales, we can also compare the density of values.This is a transnational data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail. 197â€“208, 2012 (Published online before print: 27 August 2012. And a good way to do this, is by creating different visualizations.The company mainly sells unique all-occasion gifts. Daqing Chen, Sai Liang Sain, and Kun Guo, Data mining for the online retail industry: A case study of RFM model-based customer segmentation using data mining, Journal of Database Marketing and Customer Strategy Management, Vol. It also helps with assessing your models later on, because to closer you are acquainted with the data’s properties, the better you’ll be able to pick up on things that might have gone wrong in your analysis (think of it as a kind of sanity-check for your data).