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 we would expec

Understanding variation is key to interpret the value stream behavior.  Not all variation is the same. Random Variation Vs Trends: Statistical Process Control     Variation These are some factors which may add variation to the process of cooking a turkey.  Every process has variation. Some causes of variation may be identified and acted upon. We can use two metrics for variation which complement each other: Manual Dice Throwing This simple exercise can help to experience process variation and understand the difference between a process change and inherent process variation. This understanding is key on management decisions to avoid both overreaction and lack of reaction. To run the exercise with actual dice print the form: Exercise: You will need a printed form and 4 dice for each team Throw 4 dice and add the outcomes Record the result in the Run Chart Repeat 50 times Join the dots in the Run Chart with a line Build the Histogram by counting the total number of dots on each group of