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Engineering Statistics Handbook Episode 5 Part 1

Tham khảo tài liệu 'engineering statistics handbook episode 5 part 1', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 3.4.3. Building Models Numerical models are explicit representations of our process model pictures In the Exploring Relationships section we looked at how to identify the input output relationships through graphical methods. However if we want to quantify the relationships and test them for statistical significance we must resort to building mathematical models. Polynomial models are generic descriptors of our output surface There are two cases that we will cover for building mathematical models. If our goal is to develop an empirical prediction equation or to identify statistically significant explanatory variables and quantify their influence on output responses we typically build polynomial models. As the name implies these are polynomial functions typically linear or quadratic functions that describe the relationships between the explanatory variables and the response variable. Physical models describe the underlying physics of our On the other hand if our goal is to fit an existing theoretical equation then we want to build physical models. Again as the name implies this pertains to the case when we already have equations representing the physics involved in the process and we want to estimate specific parameter values. processes NIST SEMATECH HOME TOOLS AI OS SEARCH ACK NEXT http www.itl.nist.gov div898 handbook ppc section4 ppc43.htm 2 of 2 5 1 2006 10 17 53 AM 3.4.3.I. Fitting Polynomial Models SEMMECH MOME rTOOLS IM SEARCH BACK NEXT http www.itl.nist.gov div898 handbook ppc section4 ppc431.htm 2 of 2 5 1 2006 10 17 54 AM 3.4.3.2. Fitting Physical Models NIST SEMATECH RemRerte HOME TOOLS AID S SEARCH BACK NEXT http www.itl.nist.gov div898 handbook ppc section4 ppc432.htm 2 of 2 5 1 2006 10 17 54 AM