Runs **Captital Cement, San**  **An tonio, TX**  **Al amo, San** 

**An tonio, TX**  **Holcim,**

**Portland CO**  1 <0.34 **0.54** 1.18 2 <0.34 **0.66** 1.67 3 <0.34 **0.78** 1.48 4 <0.34 **0.25** 0.6 5 <0.34 **0.25** 0.79 6 <0.34 **0.27** 0.87 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 Emissions (ppmvd@7%O2))

1 N i i 

### n

 

#  N 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 ni = number test runs = 6 6 6 0 0 Total Number of sources = 3 n =Total # test runs = 18 1 N i i 

### n

 

#  N17

This step is for QC only: means 0.34 0.46 1.10 #DIV/0! #DIV/0!

0.63 Mean =
Pooled Variance = 0.1839



#  2 2 1 

## 1 1 n i i 

## s x X n  

##  

 

#  1 1 

## 1 i n N ij i j 

## X x n   

##  

# 

1 1 n m 

2 1 1 s n m        1 

### 1 N i i 

### df n

 

###         

# 

2 1 1

s n m        1 

## 1 i n i ik

k i 

## x x n  

##  

# 1

N i i 

### n

 

# 

m= number future runs = 30 Term1 0.0889
Term2 0.0163

Squared root Term2 0.1278639 NOTE: 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 and 2*alpha=2*(0.01)



#  2 2 1 

## 1 1 n i i 

## s x X n  

##  

 

#  1 1 

## 1 i n N ij i j 

## X x n   

##  

# 

1 1 n m 

2 1 1 s n m        1 

### 1 N i i 

### df n

 

###         

# 

2 1 1

s n m        1 

## 1 i n i ik

k i 

## x x n  

##  

# 1

N i i 

### n

 

# t-statistic = quantile t-distribution with df degrees of freedom at .99 confidence level =

UPL POOLED VARIANCE = 0.96

df 

## t

2
, 

## 1 1 dfp 

## X t s n m

       Emissions (ppmvd@7%O2))

0 0 0 0 0 0#DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0!

NOTE: 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 and 2*alpha=2*(0.01)= quantile t-distribution with df degrees of freedom at .99 confidence level = 2.566933975UPL Pooled Variance= 

# 2

, 

# 1 1 dfp 

# X t s n m         2
, 

# 1 1 dfp 

# X t s n m        Runs **Captital Cement, San**  **An tonio, TX**  1 <0.34 2 <0.34 3 <0.34 4 <0.34 5 <0.34 6 <0.34 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 Emissions (ppmvd@7%O2))

1 N i i 

### n

 

#  N 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 ni = number test runs = 6 0 0 0 0 Total Number of sources = 3 n =Total # test runs = 6 1 N i i 

### n

 

#  N5

This step is for QC only: means 0.34 #DIV/0! #DIV/0! #DIV/0! #DIV/0!

0.34 Mean =
Pooled Variance = 0.0000



#  2 2 1 

## 1 1 n i i 

## s x X n  

##  

 

#  1 1 

## 1 i n N ij i j 

## X x n   

##  

# 

1 1 n m 

2 1 1 s n m        1 

### 1 N i i 

### df n

 

###         

# 

2 1 1

s n m        1 

## 1 i n i ik

k i 

## x x n  

##  

# 1

N i i 

### n

 

# 

m= number future runs = 30 Term1 0.2000
Term2 0.0000

Squared root Term2 0 NOTE: 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 and 2*alpha=2*(0.01)



#  2 2 1 

## 1 1 n i i 

## s x X n  

##  

 

#  1 1 

## 1 i n N ij i j 

## X x n   

##  

# 

1 1 n m 

2 1 1 s n m        1 

### 1 N i i 

### df n

 

###         

# 

2 1 1

s n m        1 

## 1 i n i ik

k i 

## x x n  

##  

# 1

N i i 

### n

 

# t-statistic = quantile t-distribution with df degrees of freedom at .99 confidence level =

UPL POOLED VARIANCE = 0.34

df 

## t

2
, 

## 1 1 dfp 

## X t s n m

       Emissions (ppmvd@7%O2))

0 0 0 0 0 0#DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0!

NOTE: 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 and 2*alpha=2*(0.01)= quantile t-distribution with df degrees of freedom at .99 confidence level = 3.364929997UPL Pooled Variance= 

# 2

, 

# 1 1 dfp 

# X t s n m         2
, 

# 1 1 dfp 

# X t s n m        