Polyhedrika

  Correlation is a mutual relationship or connection between two or more continuous variables. Regression is a mathematical model to define that relationship. Process Data Analysis analyzed transfer functions Y = f ( X ) where X was an attribute. Now we will analyze the case of X being a variable. Download Excel file Regression.xlsx from OneDrive to your PC to run the following examples. Correlation We have collected Natural Gas Demand data in sheet Correlation : This is actual daily demand during the month of January and the average local temperature recorded on those days.  From the date time stamp we have computed the day of the week (1 being Monday).  We are looking for factors that may affect demand and two possible factors may be Temperature and DOW. We will use Excel Data Analysis: Correlation Results: We detect a negative ( - 0.85 ) significant correlation between demand and temperature: the lower the temperature the higher the natural gas demand. This is what ...

  After we have identified what needs to be improved in our value stream we want to look for the root cause of problems. Due to the existence of variation we will need statistical data analysis. Microsoft Excel provides effective data analysis tools we can effectively use to do this.  The steps for value stream improvement are: Map it as it is really happening today in Gemba with a Value Stream Map . Collect process data in the line. To understand the value stream dynamic behavior we will need statistically significant data to enable simulation   Check for stability with Statistical Process Control Know to what extent it is able to meet the customer requirements with Process Capability Perform additional data analysis to get to the root cause Now we will continue our value stream data analysis both for variables and attribute data. Hypothesis Testing A comparison statement is composed of two hypothesis: Null hypothesis             ...