Power BI app for Tolerance Intervals and Reduced Major Axis Regression

<p>In-line inspection (ILI) tools that run internally in the pipe detect and characterize threats on a pipeline but are prone to inherent variability. The results of these ILI surveys are used to assess the criticality of reported anomalies, but the ILI runs should be compared to actual field excavations among other comparisons. To effectively manage the threats, correlation between ILI runs, and correlation between ILI and Field excavation results are important. Key to assessing how well results compare are tolerance intervals that, with a specified confidence level, cover a given proportion of the population. In this Power BI (PBI) bias assessment app 95% confidence and 80% population coverage is used. This meshes well with industry requirements. Another new added feature is least squares regression. However, often a better result for error prone data is reduced major axis regression. Both regression approaches are used to assess the relative fits of the various data types in the model.</p>