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- 1. © 2013 National Ecological Observatory Network, Inc. ALL RIGHTS RESERVED. USING EXCEL AND R FOR UNCERTAINTY ANALYSIS Josh Roberti jroberti@neoninc.org
- 2. © 2013 National Ecological Observatory Network, Inc. ALL RIGHTS RESERVED. SOFTWARE DEVELOPED BY THE NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY (NIST): • MetRology (Will Guthrie, Hung-Kung Liu, et al. of NIST) http://www.nist.gov/itl/sed/gsg/metrology.cfm http://www.nist.gov/itl/sed/gsg/metrology-for-microsoft-excel.cfm • Installation process - Email sent to all attendees on 7 Aug 2014 • Test example – did this work for everyone? • Please feel free to interrupt me with questions at any time
- 3. © 2013 National Ecological Observatory Network, Inc. ALL RIGHTS RESERVED. EXCEL:
- 4. © 2013 National Ecological Observatory Network, Inc. ALL RIGHTS RESERVED. EXCEL:
- 5. © 2013 National Ecological Observatory Network, Inc. ALL RIGHTS RESERVED. EXCEL AND R: • Brief examples. • Input quantity slip-ups • Sensitivity analysis • Variance decomposition • “Approximate Attained confidence” • Errors and warnings
- 6. © 2013 National Ecological Observatory Network, Inc. ALL RIGHTS RESERVED. EXCEL OR R: • Exercise.
Notas del editor
- A quick background on what is going to be presented
- Did everyone download and install correctly. If so, move on, if not, allow for 5-10 minutes for installation (1.5 min; possibly longer for installations)
- Open a blank excel notebook. Scroll over on the top toolbar to “metRology” and then click on GUM uncertainty analysis. All other options should say “coming soon.” Other sub-packages will not be available for a while - Will G; 7 Aug 2014.
- Provide a quick example of a blank Uncertainty analysis workbook. You can alter the amount of variables etc. Explain what each of the input / output boxes mean. Variable names (can be altered) Units – these can be arbitrary for the example, however, when dealing with multiple variables it might be a good idea to include these Input variable – self explanatory Standard uncertainty – self explanatory Degrees of freedom – if Type A, these will be n-1 from the first hand statistical analysis; if Type B, we should err towards a “larger,” but realistic number (e.g., 100+) – show an example where we change around the degrees of freedom for the different variables and see how it changes the results, etc.
- Show a “hands-on” example to demonstrate how to correctly input all of the data and also. Intentional errors – input variable name #1 should be x1, however, I have it entered as xI. This will result in an error. After this is fixed we will be able to run the example properly Show how to input correlated values – what happens to the variance decomposition (contributions)? Go over the other features of this excel workbook.
- Provide data for an exercise: give students time to do the exercise in either R or excel