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Turning Exploratory Data Analysis Tukey into Your Advantage

exploratory data analysis tukey

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It can happen that in order to extract information statisticians have to leave their comfort zone. This is what John Tukey was suggesting with exploratory data analysis. Tukey believed that by taking a step past modeling the data can be reviewed with the possibility of additional hypotheses been formed. The exploratory data analysis as well as predictive data analysis or mechanistic analysis would go beyond testing.

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The Exploratory Data Analysis Techniques

Exploratory data analysis encourages hypothesis about causes. It furthermore provides the foundation by which for the data collection can be done. Tools such as run charts and histograms are used as well as other statistical graphics, but the primary focus is to generate new hypothesis. In many ways this is a philosophy and the techniques are used to expand on it. Instead of seeking out models that the data may fall into, the data sets will make known what are the models. Research is not constricted by trying to fit data into set patterns. The data itself tells you and you can have a more open-minded approach that encourages questioning.

Exploratory Data Analysis Tukey Promoted Has Merits

Considering philosophy is nice, but is there any advantage to using the exploratory data analysis Tukey advocated? One area is quality engineering. Tukey’s insistence on the creation of hypothesis can help you as a quality engineer better generate possible root causes of any number of quality problems. Root cause analysis can begin with exploratory data analysis techniques, and other statistical tools can later be used, to confirm the hypothesis.

Exploratory Data Analysis and Data Mining

The last few years have generated a serious benefit for exploratory data analysis, which is not encumbered by a priori speculations. Success in the modern economy relies heavily on determining the tastes and expectations of the consumer. Enormous amounts of data are collected from surveys and other investigative tools. The hope is that in getting real-time statistics from consumers, future trends can be anticipated customer service improvements made. Exploratory data analysis swings the doors wide open.

Hypothesis can be developed that can be later confirmed. It becomes open territory and that’s important in the new global economy. There is already a fair amount of uncertainty and many things don’t fit into very neat categories. Letting the data tell you, rather than having a model show you, can help you generate more consumer oriented strategies. Methods of graphical data visualization can be extremely important in finding information in data sets that have no structure. Time is of the essence in the modern marketplace and the graphic tools of exploratory data analysis such as brushing, can result in considerable time saving. Verification can be used to test any model that may be emerging from the exploratory data analysis.

The advantages of this form of analysis is the ability to take overwhelming amounts of data and get some ideas from the sets and possible questions. A bonus is extraordinary data analysis can move a little bit faster than the other statistical tools.

That is extremely important because the global economy is not only diverse, but is also split-second fast. Being able to data mine more effectively and produce necessary hypothesis can give a competitive edge!