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This article was contributed by Jessica Davis.
This article was contributed by Vaibhav Waghmare
Multiple linear regression analysis is one of the most versatile tools in the data scientist's arsenal. It is very easy to apply - any one with a basic comfort level in using MS Excel can do it - and by the same token very easy to overuse and/or abuse. Abuse comes from incorrectly applying the regression model as well as incorrectly interpreting the results from a correctly applied model.
(This article was contributed by Vaibhav Waghmare)
In an earlier article we described why it is very important for many manufacturing businesses to accurately track their labor costs. A large portion of the work in small contract manufacturing companies depends on tasks such as assembly and inspection. For small companies, automation such as robots is not really a viable option and they still depend upon human effort for such mundane tasks.
In a previous article we discussed how text mining can help with customer segmentation when used in conjunction with traditional survey analysis data. In this article we will demonstrate that doing so can significantly improve the predictability of models.
This article was contributed by Vaibhav Waghmare.
Handling time series analysis in a tool like RapidMiner requires advanced skills. Basically, one has to become very conversant with the Windowing operator and other "Series" extension tools, about 80+ different ones. While basic time series forecasting tools, such as exponential smoothing are available as built-in operators, handling advanced techniques like ARIMA, requires some extensive workarounds. There are certain aspects of RapidMiner which are "non-conventional", particularly for time series. For people who do not want to give up the traidtional way of doing time series, have no fear, RapidMiner will allow you to keep your conventional methods by allowing you to fully integrate with standard methods.
Understanding the needs of your customers is a critical aspect of business. This requires proper customer segmentation. There are many different approaches to segmenting customers: based on their behavior, based on their business structures (e.g. small, medium, large) or even based on the amount of revenues they generate for you, as performed in an 80-20 customer analysis.
One of the reasons why your business would need cost modeling is to develop an automated or semi-automated bid response process. Your customers ask you to quote on a particular product and unless you can accurately figure out the prices of all the raw materials, commodities, labor and transportation, it would be difficult to generate a quote.