1 / 11

Phosphorus Volatility: EOT P Retention vs Loss Precision Analysis

This analysis compares the precision of EOT P retention and loss, using different data subsets and regression analysis, to determine their effectiveness in measuring phosphorus volatility.

abeeson
Download Presentation

Phosphorus Volatility: EOT P Retention vs Loss Precision Analysis

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. IIIG Phosphorus Volatility AnalysisRetention Versus Loss D. Boese February 29, 2008

  2. General • Data • Taken from TMC website (IIIG P Volatility.csv) • Data set includes 151 observations, 148 of which include complete information (Oil Level, Ca and P for all time periods). • Analysis consists of comparisons of precision of EOT P Loss and EOT P Retention. • P Retention (%) is a relative measure of Phosphorus volatility and P Loss (g) is an absolute measure.

  3. EOT P Retention Versus Loss Precision Analysis There are several ways to compare precision. • For each method, three sets of calculations are made based on different data subsets: • All Testkeys in Phosphorus database • All Testkeys other than 60251 which has the following Ca results for the initial through the EOT time periods, respectively: 0.2000, 0.2300, 0.2953, 0.7625, 0.2477, and 0.3205. The P Loss for this Testkey is negative. • All Testkeys excluding outliers (studentized residual greater than 3) which are 50623, 52878, 60251. The purpose of this group is to determine if deletion causes a dramatic change in the ranking of methods. • The following methods are in order of descending preference. Only the first two methods provide information regarding discrimination among oils.

  4. EOT P Retention Versus Loss Precision Analysis 1. Power curves for Oils 434 and 435. • Power (1 – β) is probability of correctly rejecting null hypothesis of equality. • It is assumed that the same number of tests are performed on each oil (number of observations). • Via Regression Analysis (all data): • P Loss: • RMSE = 0.164g • Oil 434 LS Mean = 1.13g • Oil 435 LS Mean = 0.83g • P Retention: • RMSE = 2.29% • Oil 434 LS Mean = 75.7% • Oil 435 LS Mean = 82.3% • For β = 0.1, P Loss requires 4 observations per oil whereas P Retention requires 3 observations. • Via Regression Analysis (omitting Testkey 60251): • P Loss: • RMSE = 0.129g • Oil 434 LS Mean = 1.16g • Oil 435 LS Mean = 0.83g • P Retention: • RMSE = 2.30% • Oil 434 LS Mean = 75.7% • Oil 435 LS Mean = 82.3% • The Power of P Retention is slightly higher than that of P Loss.

  5. EOT P Retention Versus Loss Precision Analysis (Continued) 1. Power curves for Oils 434 and 435 (continued). • Via Regression Analysis (omitting outliers: Testkeys 50623, 52878, and 60251) • P Loss: • RMSE = 0.108g • Oil 434 LS Mean = 1.16g • Oil 435 LS Mean = 0.83g • P Retention: • RMSE = 1.98% • Oil 434 LS Mean = 75.7% • Oil 435 LS Mean = 82.1% • For β = 0.1, both methods require 2 observations per oil.

  6. EOT P Retention Versus Loss Precision Analysis (Continued) 2. Anticipated range of results versus variability. • Assume Oil 434 at the high end of the range for volatility and no volatility at the other end of the range. • Desire Range to Variability Ratio (R/V) to be high. • Utilize RMSE as estimate for variability and Oil 434 LS Means as estimate of Oil 434 mean. • R/Vs of P Retention are slightly better than those of P Loss. 3. Number of outliers (studentized residuals with magnitude of 3 or higher): • Does not take into account ability to discriminate among oils of interest. • Utilized the regression analysis of P Loss and P Retention with Lab and Oil as predictors. • P Loss had one additional outlier (Testkey 60251 which had ahigh level of Ca at 60 hours).

  7. EOT P Retention Versus Loss Precision Analysis (Continued) 4. Coefficient of Variability (CV = Standard Deviation/Mean) • Does not take into account ability to discriminate among oils of interest. • Is the only criteria of the four that is scale dependent, i.e., if 1000 is added, or if the result is subtracted from 100 (P Ret converted to P Loss), a much different CV results though discrimination remains unchanged. • Due to the above two items, this method is not preferred. • Utilize RMSE and Mean of all Responses. • CV of P Loss compares favorably to that of P Retention.

  8. Comparison of Phosphorus Volatility and IIIG Precision (All Data) • For purposes of comparison to an existing test, precision data were calculated for the IIIG critical parameters using the same Testkeys. No outliers were excluded. • The power statistic was calculated for each of the three pairs of oils. • The power of P Retention and P Loss compare favorably to the IIIG parameters.

  9. Comparison of Phosphorus Volatility and IIIG Precision (Omitting 60251) • Precision calculations are made on all parameters omitting Testkey 60251. • The main change is that the power of the P Loss improved slightly resulting in the same number of tests (3) as for P Retention to yield a power of greater than 0.9.

  10. Conclusions • The four precision statistics considered in this analysis slightly favor EOT P Retention to EOT P Loss. • In general, either Phosphorus Volatility method provides better discrimination of reference oils than the IIIG tests. • Though the statistics slightly favors EOT P Retention, P Loss is more of a direct assessment of the amount of P being volatilized if oils with different P contents are compared.

More Related