Spreadsheet: 075485dd-293e-4014-8477-a07d2820c007
Sheet: Sheet1

Unnamed: 0 | Unnamed: 1 | Unnamed: 2 | Unnamed: 3 | Unnamed: 4 | Unnamed: 5 | Unnamed: 6 | Unnamed: 7 | Unnamed: 8 | Unnamed: 9 | Unnamed: 10 | Unnamed: 11
 |  |  |  |  | Template for Entering Candidate Method Test
 |  |  |  |  | Data and Calculating Test Results Related to a
 |  |  |  |  | Request for Approval of an Approved Regional
 |  |  |  |  | Method (ARM) for PM2.5 [40 CFR 58, [NAME]] |  |  |  |  |  | "Small"   [NAME]. 122
 |  | Instructions
 |  | This suite of spreadsheets is intended for entering and analyzing field test data obtained from the Comparability tests required for Class III candidate approved regional methods (ARMs) for PM2.5, according to new regulatory provisions of 40 CFR Part 58, [NAME] that became effective on December 18, 2006.  (See Section 2.4 of Appendix C to Part 58, (U.S. Federal Register, Volume 71, October 17, 2006, page 61313).
 |  | This spreadsheet is designed to run on Excel 2003 (with zoom set to 100%).  It appears to run properly on Excel 2000, but the [NAME] (if used) and Regression sheets must be unprotected (Tools>Protection>Unprotect Sheet) to make the data filters work. Also, for best viewing, the zoom should be set to 75%.
 |  | 1.  Enter applicant, candidate method, site, sampling frequency, and other identification information in the "Title" tab.
 |  | 2.  The test data should be in the form of daily "data sets" consisting of nominal 24-hour integrated ambient PM concentration measurements, with each set containing at least 1 FRM measurement and at least 1 collocated and concurrent candidate FEM measurement, in μg/m3.  A minimum of 90 data sets are required.  Data sets having a mean FRM concentration measurement less than 3 μg/m3 should be entered to count towards the 90-set minimum, but such data sets may be excluded from the regression analysis on the "Regression" tab -- by deleting the "ok" in the Validity column.
 |  | 3.  If the daily data sets contain only 1 FRM measurement or 1 candidate ARM measurement, the single-measurement data may be optionally entered directly in the "Regression" tab in the appropriate "Data set means" column (enter any comments in the cell to the right) rather than in the "Raw FRM data" or "Raw candidate data" tabs.  However, note that doing so will permanently override any corresponding data entered on the Raw data sheets.   Note also that precision cannot be calculated for single-measurement FRM or single-measurement candidate data sets.
 |  | 4. If the daily data sets include multiple FRM or multiple candidate ARM measurements, enter the FRM data first (if multiple) at the "Raw FRM data" tab, because the test dates associated with each data set will then be automatically carried to the "Raw candidate data" sheet.  Then enter the candidate method data (if multiple) at the "Raw Candidate data" tab. Use the Comments columns to enter any possibly pertinent information about any of the measurements in either the FRM or Candidate data subset.
 |  | 5. If 2 or more FRM measurements are entered for a data set, the data are automatically checked according to an outlier test, and the mean and precision are calculated.  The outlier test results are for information purposes only and are not used in any test results.  Do not delete any invalid data sets on this "Raw FRM data" tab; invalid data sets will be filtered out later on other sheets.
 |  | 6. This spreadsheet allows for entry of up to 122 data sets (one year of 1:3 data).  If more than 122 data sets will be required, the full spreadsheet should be used.  Note that the summary statistics at the bottom of the spreadsheet are for informational purposes only as they include any invalid data sets.  The formal summary statistics using only valid data are calculated in the "Precision" (if applicable) and "Regression" tabs.
 |  | 7. Similarly, enter the multiple candidate ARM data at the "Raw candidate data" tab.  Again, the mean and precision are calculated, and an outlier test will check the data, but the outlier test results are ignored for test purposes. Do not delete any invalid data sets on this "Raw candidate data" tab as invalid data sets will be filtered out in other tabs.   Note that the summary statistics at the bottom of the spreadsheet are for informational purposes only as they include any invalid data sets.  The formal summary test statistics using only valid data are calculated in other tabs.
 |  | 8. If multiple FRM or candidate ARM method measurements are entered for each data set, the mean concentrations for the FRM and/or candidate ARM methods for each data set are presented in the "Precision" tab, along with both the absolute precision (μg/m3) and relative precision (CV), with the later precision (CV) being the relevant one for purposes of characterizing the candidate ARM.  Important: all invalid data sets must be filtered out in the "Precision" tab so that the test result calculations will be correct at the bottom of the sheet.  Follow the instructions in the box in the upper right corner of the sheet.
 |  | 9. The required linear regression calculations are carried out in the "Regression" tab.   Important: all invalid data sets must be filtered out in the "Regression" tab so that the test result calculations will be correct at the bottom of the sheet.  Follow the instructions in the box in the upper right of the sheet.  Data sets having FRM concentrations less than 3 ug/m3 may be excluded, if desired, from the test but can still be counted against the 90 set minimum.  To exclude such low concentration data sets, change "ok" to "x" in the "Regression" tab, then click on the ▼ filter in the Validity column and select "ok."
 |  | 10. If new data are entered after filtering out the invalid data sets, click on the ▼ in the  "Data set Validity" column of both the Precision (if applicable) and Regression tabs, then click on "all" to include the new data.  Then click on ▼ and "ok" again to filter out the invalid data sets.
 |  | 11. Required data calculations for the ARM test results are presented on the "Summary" tab, along with the test requirements and a "pass" or "fail" indication.  Charts present the regression results graphically.  If the charts do not plot correctly, follow the instructions at the bottom of the "Summary" sheet.  If the data sets contain only single candidate method measurements, precision for the candidate method cannot be determined and must be obtained from other data.
 |  |  |  |  |  |  | Version 0.3 - 3/15/07  [NAME], RTI International; T. Hanley, US EPA