Statistical Models in Chemical Engineering

The models based on the equations of transport phenomena and on stochastic models contain an appreciable quantity of mathematics, software creation, computer programming and data processing. 

Descriptive statistics. A series of physical measurements can be described numerically. If for example, we have recorded the concentration of 1000 different samples in a research problem, it is not possible to provide the user with a table giving all 1000 results. In this case, it is normal to summarize the main trends. This can be done not only graphically, but also by considering the overall parameters such as mean and standard deviation, skewness etc. Specific values can be used to give an overall picture of a set of data. 

Distribution for random variables. The concept of distribution is fundamental to statistics. If a series of measurements is extracted from a great number of similar non-produced measurements (called population), we obtain a population sample. However, it is not possible to have the same mean characteristics for all the sam- 

Chemical Engineering. Tanase G. Dobre and Jos G. Sanchez Marcano Copyright 2007 WILEY-VCH Verlag GmbH Co. KGaA, Weinheim ISBN 978-3-527-30607-7 

If the number of samples with characteristics presenting a normal distribution is not significant, then we can have an error structure. This situation can also be due to outliers, i.e. samples that are atypical of the population or that might have been incorrectly labeled or grouped. 

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I 5 Statistical Models in Chemical Engineering Table 5.2 Continued. 

I 5 Statistical Models in Chemical Engineering Table 5.44 Synthesis of the analysis of variances for two factors - Example 5.6.2. 

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