ANALYTICAL CHEMISTRY FINAL- ACS EXAM 2022
1. ppm : ans>> (grams analyte/grams sample)x10^6
2. Molarity : ans>> moles analyte/liter of solution
3. Volume Percent : ans>> (volume solute/volume soution)x100
4. Volume ppm : ans>> (volume solute/volume solution)x10^6
5. kilo- : ans>> 10^3
6. deci- : ans>> 10^-1
7. centi- : ans>> 10^-2
8. milli- : ans>> 10^-3
9. micro- : ans>> 10^-6
10. nano- : ans>> 10^-9
11. pico- : ans>> 10^-12
12. femto- : ans>> 10^-15
13. weight percent : ans>> (grams analyte/grams sample)x100
14. ppt : ans>> (grams analyte/grams sample)x10^3
15. ppt simplified : ans>> gram analyte/liter solution
16. ppm simplified : ans>> mg analyte/liter solution
17. ppb simplified : ans>> micrograms analyte/liter solution
18. pptr simplified : ans>> nanograms analyte/liter solution
19. buoyancy correction : ans>> m=(m'(1-(air density/weight density)))/(1-(air
density/ob- ject density))
20. accuracy : ans>> closeness of the mean to the "true value"
21. precision : ans>> reproducibility of individual measurements
22. Uncertainty in Addition/Subraction : ans>> e=sqrt(ex1^2+ex2^2+ex3^2+...)
23. Uncertainty in
Multiplication/Division : ans>> e=y*sqrt((ex1/x1)^2+(ex2/x2)^2+(ex3/x3)^2+...)
24. Significant Figures in Logarithms and antilogarithms : ans>> the number
of signif- icant figures in the log should equal the number of digits in the mantissa
25. How many significant figures in log(205.5) : ans>> four significant figures,
so you will need four decimal places in your answer
26. pH : ans>> -log[H3O+]
27. [H3O+] : ans>> 10^-pH
28. Absorbance : ans>> -log(transmittance)
29. Random Error : ans>> -repeated measurements are sometimes high and
sometimes low
-cannot be corrected for
30. Systematic Error : ans>> -repeated measurements are usually always high
or always low
,ANALYTICAL CHEMISTRY FINAL- ACS EXAM 2022
-can and should be corrected for
31. Relative uncertainty= : ans>> absolute uncertainty/magnitude of measureme
,ANALYTICAL CHEMISTRY FINAL- ACS EXAM 2022
32. 68% of measurements in a Gaussian Curve will lie : ans>> between the
mean-1 and the mean+1
33. Variance in standard deviation : ans>> standard deviation squared
34. mean= : ans>> true value +-time*standard deviation
35. T-test Case 1 : ans>> measure sample of known composition
36. T-test case 2 : ans>> compare replicate measurement of an unknown sample
37. T-test case 3 : ans>> compare individual difference of an unknown sample
- two sets of data analyzed by both methods being used
38. T-test case 1 equation : ans>> true value= mean (+-)
(time*standard devia- tion)/sqrt(number of measurements))
39. T-test case 1 Tcalc= : ans>> (sqrt(n)Iknown value-calculated
meanI)/standard devia- tion
40. For Case 1 : ans>>
If Tcalc>Ttable : ans>> the actual value isn't in the range and it is bad
41. For Case 1 : ans>>
If Tcalc<Ttable : ans>> the actual value is close to our calculated value
42. For Case 2 : ans>>
you need to first solve for Fcalc= : ans>> (larger standard deviation)^2/(smaller
standard deviation)^2
43. If Fcalc<Ftable, you should use : ans>> Case 2A
44. If Fcalc>Ftable, you should use : ans>> Case 2B
45. T-Test Case 2A : ans>> Tcalc= : ans>> (Icalculated mean 1-
calculated mean 2I/spooled)*sqrt((n1*n2)/(n1+n2))
46. For Case 2A : ans>>
if Tcalc < Ttable, then : ans>> the two sets of data are statistically indistinguishab
47. For Case 2A : ans>>
spooled(standard deviation pooled)= : ans>> sqrt((s1^2(n1-1)+s2^2(n2-
1))/(n1+n2-2)) where s=standard deviation and n=number of measurements
48. For Case 2B : ans>>
Tcalc= : ans>> (Icalculated mean 1-calculated mean 2I)/sqrt((s1^2/n1)+(s2^2/n2))
49. For case 2B : ans>>
if Tcalc<Ttable, then : ans>> the two sets of data are indistinguishable
50. For Case 3 : ans>>
Sd= : ans>> sqrt((sum of (difference-average difference)^2)/n-1)
51. For Case 3 : ans>>
Tcalc= : ans>> (Iaverage differenceI/Sd)*sqrt(n)
52. Q-test : ans>> Q=gap/range
1. ppm : ans>> (grams analyte/grams sample)x10^6
2. Molarity : ans>> moles analyte/liter of solution
3. Volume Percent : ans>> (volume solute/volume soution)x100
4. Volume ppm : ans>> (volume solute/volume solution)x10^6
5. kilo- : ans>> 10^3
6. deci- : ans>> 10^-1
7. centi- : ans>> 10^-2
8. milli- : ans>> 10^-3
9. micro- : ans>> 10^-6
10. nano- : ans>> 10^-9
11. pico- : ans>> 10^-12
12. femto- : ans>> 10^-15
13. weight percent : ans>> (grams analyte/grams sample)x100
14. ppt : ans>> (grams analyte/grams sample)x10^3
15. ppt simplified : ans>> gram analyte/liter solution
16. ppm simplified : ans>> mg analyte/liter solution
17. ppb simplified : ans>> micrograms analyte/liter solution
18. pptr simplified : ans>> nanograms analyte/liter solution
19. buoyancy correction : ans>> m=(m'(1-(air density/weight density)))/(1-(air
density/ob- ject density))
20. accuracy : ans>> closeness of the mean to the "true value"
21. precision : ans>> reproducibility of individual measurements
22. Uncertainty in Addition/Subraction : ans>> e=sqrt(ex1^2+ex2^2+ex3^2+...)
23. Uncertainty in
Multiplication/Division : ans>> e=y*sqrt((ex1/x1)^2+(ex2/x2)^2+(ex3/x3)^2+...)
24. Significant Figures in Logarithms and antilogarithms : ans>> the number
of signif- icant figures in the log should equal the number of digits in the mantissa
25. How many significant figures in log(205.5) : ans>> four significant figures,
so you will need four decimal places in your answer
26. pH : ans>> -log[H3O+]
27. [H3O+] : ans>> 10^-pH
28. Absorbance : ans>> -log(transmittance)
29. Random Error : ans>> -repeated measurements are sometimes high and
sometimes low
-cannot be corrected for
30. Systematic Error : ans>> -repeated measurements are usually always high
or always low
,ANALYTICAL CHEMISTRY FINAL- ACS EXAM 2022
-can and should be corrected for
31. Relative uncertainty= : ans>> absolute uncertainty/magnitude of measureme
,ANALYTICAL CHEMISTRY FINAL- ACS EXAM 2022
32. 68% of measurements in a Gaussian Curve will lie : ans>> between the
mean-1 and the mean+1
33. Variance in standard deviation : ans>> standard deviation squared
34. mean= : ans>> true value +-time*standard deviation
35. T-test Case 1 : ans>> measure sample of known composition
36. T-test case 2 : ans>> compare replicate measurement of an unknown sample
37. T-test case 3 : ans>> compare individual difference of an unknown sample
- two sets of data analyzed by both methods being used
38. T-test case 1 equation : ans>> true value= mean (+-)
(time*standard devia- tion)/sqrt(number of measurements))
39. T-test case 1 Tcalc= : ans>> (sqrt(n)Iknown value-calculated
meanI)/standard devia- tion
40. For Case 1 : ans>>
If Tcalc>Ttable : ans>> the actual value isn't in the range and it is bad
41. For Case 1 : ans>>
If Tcalc<Ttable : ans>> the actual value is close to our calculated value
42. For Case 2 : ans>>
you need to first solve for Fcalc= : ans>> (larger standard deviation)^2/(smaller
standard deviation)^2
43. If Fcalc<Ftable, you should use : ans>> Case 2A
44. If Fcalc>Ftable, you should use : ans>> Case 2B
45. T-Test Case 2A : ans>> Tcalc= : ans>> (Icalculated mean 1-
calculated mean 2I/spooled)*sqrt((n1*n2)/(n1+n2))
46. For Case 2A : ans>>
if Tcalc < Ttable, then : ans>> the two sets of data are statistically indistinguishab
47. For Case 2A : ans>>
spooled(standard deviation pooled)= : ans>> sqrt((s1^2(n1-1)+s2^2(n2-
1))/(n1+n2-2)) where s=standard deviation and n=number of measurements
48. For Case 2B : ans>>
Tcalc= : ans>> (Icalculated mean 1-calculated mean 2I)/sqrt((s1^2/n1)+(s2^2/n2))
49. For case 2B : ans>>
if Tcalc<Ttable, then : ans>> the two sets of data are indistinguishable
50. For Case 3 : ans>>
Sd= : ans>> sqrt((sum of (difference-average difference)^2)/n-1)
51. For Case 3 : ans>>
Tcalc= : ans>> (Iaverage differenceI/Sd)*sqrt(n)
52. Q-test : ans>> Q=gap/range
