Applied Statistical Methods and the Chemical Industry
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believe that statistical tools can help them be The discipline of statistics is the study of effective in their work. This chapter will begin with some simple effective methods of data collection, data of modem descriptive statistics, includideas summarization, and (data based, quantitative) and graphical data summarizanumerical ing inference making in a framework that explicthe notions of fitting equations and tools, tion itly recognizes the reality of nonnegligible theoretical distributions. using and data to variation in many real-world processes and industrial process routine for tools some Next, measurements. concenassessment, capability and monitoring The ultimate goal of the field is to provide chartcontrol of notion the on primarily trating tools for extracting the maximum amount of followed be will This presented. be will ing, useful information about a noisy physical of common staprocess from a given investment of data col- by a more extensive discussion and data strategies collection data tistical lection and analysis resources. It is clear that experimental multifactor for methods analysis such a goal is relevant to the practice of indusmet in both laboratory and productrial chemistry. The primary purposes of this situations environments. This section will touch on chapter are to indicate in concrete terms the tion of partitioning observed variation in a ideas nature of some existing methods of applied response to various sources thought to system statistics that are particularly appropriate to the response, factorial and fractional influence industrial chemistry, and to provide an entry experimental designs, sequential factorial into the statistical literature for those readers strategy, screening experiments, experimental who find in the discussion here reasons to and response surface fitting and representation. Next come brief discussions of two types *Iowa State University, Departments of Statistics and of special statistical tools associated specifiof Industrial Engineering and Manufacturing Systems cally with chemical applications, namely, mixEngineering. ture techniques and nonlinear mechanistic **Dow Chemical Company. INTRODUCTION
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Riegel Handbook of Industrial Chemistry, I Oth Edition Edited by Kent. Kluwer Academic/Plenum Publishers, New York 2003
APPLIED STATISTICAL METHODS AND THE CHEMICAL INDUSTRY 51
A simple plot of aluminum content against time order, often called a run chart, is a natural place to begin looking for any story carried by a data set. Figure 4.1 shows such a plot for the data of Table 4.1, and in this case reveals only one potentially interesting feature of the data. That is, there is perhaps a weak hint of a downward trend in the aluminum contents that SIMPLE TOOLS OF DESCRIPTIVE might well have been of interest to the original STATISTICS researchers. (If indeed the possible slight decline in aluminum contents is more than or There are a variety of data summarization description methods whose purpose is to "random scatter," knowledge of its physical orimake eviden
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