Analytical Chem istry - DePauw University

Chapter 5 Standardizing Analytical Methods207SUMMARY OUTPUTRegression StatisticsMultiple R 0.99979366R Square 0.99958737Adjusted R Square 0.99948421Standard Error 0.00199602Observations 6ANOVAdf SS MS F Significance FRegression 1 0.0386054 0.0386054 9689.9103 6.3858E-08Residual 4 1.5936E-05 3.9841E-06Total 5 0.03862133Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%Intercept 0.00139272 0.00144059 0.96677158 0.38840479 -0.00260699 0.00539242 -0.00260699 0.00539242Cstd 29.5927329 0.30062507 98.437342 6.3858E-08 28.7580639 30.4274019 28.7580639 30.4274019Figure 5.28 Excel’s summary of the regression results for Practice Exercise 5.6.The standard deviation in C A is1.996×10s CA=29.591 1 ( 0. 114−0. 1183)+ += 4.772× 10−23 6 ( 29. 59) × ( 4.408×10 -5 )−3 2and the 95% confidence interval isµ CC tsA A C A−3 −5= ± = 380 . × 10 ± { 278 . × ( 4. 772×10 )}−= 3. 80× 10 M± 013 . × 10Click here to return to the chapterPractice Exercise 5.73 −3Figure 5.29 shows an R session for this problem, including loading thechemCal package, creating objects to hold the values for C std , S std , andSsamp. Note that for Ssamp, we do not have the actual values for thethree replicate measurements. In place of the actual measurements, wejust enter the average signal three times. This is okay because the calculationdepends on the average signal and the number of replicates, and noton the individual measurements.Click here to return to the chapterM5