Translating Statistics to Make Decisions by Victoria Cox

Author:Victoria Cox
Language: eng
Format: epub
Publisher: Apress, Berkeley, CA

© Victoria Cox 2017

Victoria CoxTranslating Statistics to Make Decisions 10.1007/978-1-4842-2256-0_7

7. Statistical Modeling

What Is Actually Going On in the Data?

Victoria Cox1

(1)Dstl, Salisbury, UK

Statistical modeling is the next step up from simple hypothesis tests; it involves a larger number of explanatory variables, a larger number of levels within each explanatory variable, or both. At this stage we are still only concerned with one response variable.

Models are fit to test the importance of different variables in relation to the response variable, to predict future outcomes, and to assign uncertainty and repeatability to the results.

For example, you may want to test if a variable has a significant effect on an outcome, or you could test what outcome may occur given an untested level of an explanatory variable, or you can assign uncertainty around the model estimates and assess how well the model fitted the data.

There are numerous statistical models and I can’t cover all the options, so I have chosen some of the more commonly used ones to discuss. Most of the models will have a similar output; the key is to use the correct model dependent on your data type, led principally by the response variable. In addition all the models will have certain assumptions that need to be satisfied.

The first section of this chapter looks at the generics of model assumptions, model structure, and model output. The second then delves into some of the commonly used models with explanations of their purpose, R examples, and interpretation of the output.

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