Lovely forecasting blog

Eight different random walks.
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I really loved this simple, smart and yet elegant explanation of forecasting. even a high school quarterback could understand it, and maybe get a internship job building and running and re running code for Mars shot.

Despite my plea that you remain svelte in real life, I implore you to be naïve in business forecasting – and use a naïve forecasting model early and often. A naïve forecasting model is the most important model you will ever use in business forecasting.

and now the killer line

Purists may argue that the only true naïve forecast is the “no-change” forecast, meaning either a random walk (forecast = last known actual) or a seasonal random walk (e.g. forecast = actual from corresponding period last year). These are referred to as NF1 and NF2 in the Makridakis text (where NF = Naïve Forecast). In our 2006 SAS webseries Finding Flaws in Forecasting, an attendee asked “What about using a simple time series forecast with no intervention as the naïve forecast?” Is that allowed?

i did write a blog article on forecasting some time back, but back then I was a little blogger, with the website name being http://iwannacrib.com

great work in helping make forecasting easier to understand for people who have flower shops and dont have a bee, to help them with the forecasts, nor an geeky email list, not 4000$.

make it easier for the little guy to forecast his sales, so he cuts down on his supply chain inventory, lowering his carbon footprint.

Blog.sas.com take a bow, on labour day, helping workers with easy to understand models.

http://blogs.sas.com/forecasting/index.php?/archives/68-Which-Naive-Model-to-Use.html

SAS Knowledge Exchange

Visual analytics : research and practice
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Here is an interesting website by SAS.com – it showcases lots of business analytics content more from a conceptual rather than a tool based perspective- have a glance yourself.

http://www.sas.com/knowledge-exchange/business-analytics/

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