Sorting the Data To Quickly Spot Extreme OutliersĪn easy way to quickly spot extreme outliers is to sort the data. A data point is often considered to be an outlier if its residual value is more than there standard deviations from the mean of the residuals. After Excel has performed the regression and calculated the residuals, further analysis will be performed to determine if any of the data points can also be considered outliers based upon any unusually large residual terms generated. An outlier should be removed if it is obviously extremely and inconsistent with the remainder of the data.Īt this point in the beginning of the analysis, the objective is to remove outliers that are obviously extreme.
Extremely outliers should be removed before beginning regression analysis. The data from the 21 trial runs are as follows:Ĭalculation of the mean is one of the fundamental computations when performing linear regression analysis. The machine was calibrated to the same settings and cleaned prior to each trial run and input plastic pellets from the same batch were used in all 21 trial runs. The same operator ran the machine on each trial run at approximately the same time during a shift. It is important to note that all trial runs were performed as identically as possible. If the relationship between quantity of input plastic pellets in each batch and the number of parts produced from each batch is linear, calculate the equation that describes that relationship. In each case a different-sized batch of plastic pellets was input into the machine and the total number of identical plastic parts produced from each batch was recorded.
The company conducted 21 independent production runs on the machine. The company would like to create an equation that will calculate the number of identical plastic parts that would be produced for a specified quantity of input plastic pellets. Prediction Interval of Simple Regression in Excel 2010 and Excel 2013Ī company has a large plastic injection molding machine. Residual Normality Tests in Excel – Kolmogorov-Smirnov Test, Anderson-Darling Test, and Shapiro-Wilk Test For Simple Linear RegressionĮvaluation of Simple Regression Output For Excel 2010 and Excel 2013Īll Calculations Performed By the Simple Regression Data Analysis Tool in Excel 2010 and Excel 2013 Residual Evaluation For Simple Regression in 8 Steps in Excel 2010 and Excel 2013 Overview of Simple Linear Regression in Excel 2010 and Excel 2013Ĭomplete Simple Linear Regression Example in 7 Steps in Excel 2010 and Excel 2013 This is one of the following seven articles on Simple Linear Regression in Excel
0 kommentar(er)
