tailieunhanh - The Microguide to Process Modeling in Bpmn 2.0 by MR Tom Debevoise and Rick Geneva_6

Tham khảo tài liệu 'the microguide to process modeling in bpmn by mr tom debevoise and rick geneva_6', kỹ thuật - công nghệ, điện - điện tử phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | . How can I test whether or not the random errors are distributed normally ENGINEERING STATISTICS HANDBOOK home TOOLS AIDS ISEAtCH BACK next 4. Process Modeling . Data Analysis for Process Modeling . How can I tell if a model fits my data . How can I test whether or not the random errors are distributed normally Histogram The histogram and the normal probability plot are used to check whether or not it is reasonable to and Normal assume that the random errors inherent in the process have been drawn from a normal PrtHmbility distribution. The normality assumption is needed for the error rates we are willing to accept when Plot Usedfor making decisions about the process. If the random errors are not from a normal distribution N rmality incorrect decisions will be made more or less frequently than the stated confidence levels for our Checks inferences indicate. Normal The normal probability plot is constructed by plotting the sorted values of the residuals versus the Probability associated theoretical values from the standard normal distribution. Unlike most residual scatter Plot plots however a random scatter of points does not indicate that the assumption being checked is met in this case. Instead if the random errors are normally distributed the plotted points will lie close to straight line. Distinct curvature or other signficant deviations from a straight line indicate that the random errors are probably not normally distributed. A few points that are far off the line suggest that the data has some outliers in it. Examples Normal probability plots for the Pressure Temperature example the Thermocouple Calibration example and the Polymer Relaxation example are shown below. The normal probability plots for these three examples indicate that that it is reasonable to assume that the random errors for these processes are drawn from approximately normal distributions. In each case there is a strong linear relationship between the residuals and the