RunsCaptitalCement, SanAntonio, TXAlamo, SanAntonio, TXHolcim,PortlandCO1 <0.340.541.182 <0.340.661.673 <0.340.781.484 <0.340.250.65 <0.340.250.796 <0.340.270.8778910111213141516Emissions(ppmvd@7%O2))17181920212223242526272829303132333435ni = number test runs =666 0 0 0 0 0Total Number of sources = 3n =Total # test runs =18171 11inNiji jXxn 11Niidf n    11ini ikkixxn1NiinNThis step is for QC only:means 0.34 0.46 1.10 #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0!0.63Mean =1 11inNiji jXxn 11Niidf n    11ini ikkixxn1NiinNPooled Variance =0.1839m=numberfutureruns= 30Term1 0.0889Term2 0.0163 22111niisx Xn 1 1n m21 1sn m   dft21 1sn m   2,1 1df pXt sn m    Squared root Term20.1278639NOTE: the pvalue for the t-statistic is calculated as: 2*alpha, where 1-alpha is desired confidence, so if 99% confidence is desired then alpha=0.01 ant‐statistic =quantilet‐distributionwithdfdegreesoffreedomat.99confidencelevel=2.566933975UPLPOOLEDVARIANCE=0.96 22111niisx Xn 1 1n m21 1sn m   dft21 1sn m   2,1 1df pXt sn m    UPL PooledVariance=2,1 1df pXt sn m    2,1 1df pXt sn m    00 0#DIV/0! #DIV/0! #DIV/0!nd 2*alpha=2*(0.01)RunsCaptitalCement, SanAntonio, TX1<0 34Emissions(ppmvd@7%O2))<0.342 <0.343 <0.344 <0.345 <0.346<0 34.7891011121314151617181920212223242526272829303132333435 22111niis xXn 1 11inNiji jXxn 11Niidf n    11ini ikkix xn1NiinNni = number test runs =600 0 0 0 0 0Total Number of sources = 3 22111niis xXn 1 11inNiji jXxn 11Niidf n    11ini ikkix xn1NiinNn =Total # test runs =6 22111niis xXn 1 11inNiji jXxn 11Niidf n    11ini ikkix xn1NiinN5 22111niis xXn 1 11inNiji jXxn 11Niidf n    11ini ikkix xn1NiinNThis step is for QC only:means 0.34 #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! 22111niis xXn 1 11inNiji jXxn 11Niidf n    11ini ikkix xn1NiinN 22111niis xXn 1 11inNiji jXxn 11Niidf n    11ini ikkix xn1NiinN0.34Mean = 22111niis xXn 1 11inNiji jXxn 11Niidf n    11ini ikkix xn1NiinN 22111niis xXn 1 11inNiji jXxn 11Niidf n    11ini ikkix xn1NiinNPooled Variance =0.0000 22111niis xXn 1 1n m21 1sn m   dft21 1sn m   2,1 1df pXt sn m    m=numberfutureruns= 30Term1 0.2000 22111niis xXn 1 1n m21 1sn m   dft21 1sn m   2,1 1df pXt sn m    Term2 0.0000 22111niis xXn 1 1n m21 1sn m   dft21 1sn m   2,1 1df pXt sn m    Squared root Term20 22111niis xXn 1 1n m21 1sn m   dft21 1sn m   2,1 1df pXt sn m    qNOTE: the pvalue for the t-statistic is calculated as: 2*alpha, where 1-alpha is desired confidence, so if 99% confidence is desired then alpha=0.01 22111niis xXn 1 1n m21 1sn m   dft21 1sn m   2,1 1df pXt sn m    t‐statistic =quantilet‐distributionwithdfdegreesoffreedomat.99confidencelevel=3.364929997UPLPOOLEDVARIANCE=0.34 22111niis xXn 1 1n m21 1sn m   dft21 1sn m   2,1 1df pXt sn m     22111niis xXn 1 1n m21 1sn m   dft21 1sn m   2,1 1df pXt sn m    UPL PooledVariance=2,1 1df pXt sn m    Variance=2,1 1df pXt sn m    2,1 1df pXt sn m    2,1 1df pXt sn m    2,1 1df pXt sn m    2,1 1df pXt sn m    2,1 1df pXt sn m    00 0#DIV/0! #DIV/0! #DIV/0!and 2*alpha=2*(0.01)