![]() ![]() Consider the data obtained from a chemical process where the yield of the process is thought to be related to the reaction temperature (see the table below). ![]() This chapter discusses simple linear regression analysis while a subsequent chapter focuses on multiple linear regression analysis.Ī linear regression model attempts to explain the relationship between two or more variables using a straight line. Additionally, DOE folios also include a regression tool to see if two or more variables are related, and to explore the nature of the relationship between them. The reason for this is explained in Appendix B. ![]() Regression analysis forms the basis for all Weibull++ DOE folio calculations related to the sum of squares used in the analysis of variance. These results, along with the results from the analysis of variance (explained in the One Factor Designs and General Full Factorial Designs chapters), provide information that is useful to identify significant factors in an experiment and explore the nature of the relationship between these factors and the response. Every experiment analyzed in a Weibull++ DOE foilo includes regression results for each of the responses. ![]() Regression analysis forms an important part of the statistical analysis of the data obtained from designed experiments and is discussed briefly in this chapter. For example, an analyst may want to know if there is a relationship between road accidents and the age of the driver. Regression analysis is a statistical technique that attempts to explore and model the relationship between two or more variables. ![]()
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