Error Analysis Example, Lab Reports of Physics

Determining the Important Errors, Example Lab Report Section on Error Analysis .

Typology: Lab Reports

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Error Analysis Example
Error analysis is always a difficult area for students. However, the careful consideration of
experimental error is one of the important skills that we need to learn to be effective scientists. In
the following discussion, the errors in a titration experiment are considered. The first section is a
detailed look at how to determine the most important errors. The second section is an example of
the corresponding text that would be written in a lab report for CH141-142.
Determining the Important Errors
The purpose of the error analysis section of the lab report is to determine the most important
errors and the effect that those errors have on the final result.
Random Errors: Random errors cause positive and negative deviations from the average
value of a measurement. Random errors cancel by averaging, if the experiment is repeated many
times. Upon averaging many trials, random errors have an effect only on the precision of a
measurement. The effect of random errors is primarily on the precision. Every non-integer
experimental measurement is a source of random error. The random error is estimated from the
readability of the device. A table of typical measurements and the associated precision, under
practical circumstances, is given below. For instrument readings, to avoid round-off error, report
one extra significant figure and then underline the digit that is not significant.
Volumetric flasks and pipettes precision (relative) significant figures
10 mL
0.03 mL 3 i.e. 10.0 mL
25 mL
0.03 mL 3 25.0 mL
50 mL
0.05 mL 3 50.0 mL
100 mL
0.08 mL 4 100.0 mL
Auto-pipettors
10
L
0.05
L (0.5%) 3 i.e. 10.0
L
100
L
0.3
L (0.3%) 3 100.
L
1000
L
2
L (0.2%) 3 1000.
L
Analytical Balance
0.1000 g
0.0001 g 4 e.g. 0.3456 g
1.0000 g
0.0001 g 5 2.3456 g
10.0000 g
0.0001 g 6 12.3456 g
Spectrophotometer (Spectro-Viz
*
)
0.100
0.003 (
3%) 2 e.g. 0.123
0.500
0.003 (
0.6%) 2 0.456
1.000
0.004 (
0.4%) 3 1.123
1.500 (1 sign. fig. for A>2)
0.015 (
1%) 2 1.567
pH Meter
7.00
0.02 ~3 e.g. 6.123
Electronic Pressure Sensor
1.0 atm (760 torr)
0.0005 atm (
0.4 torr) 3-4 e.g 826.4 torr
Constant Current Power Supply
0.400 amp
0.0004 amp (
0.1 %) 3 0.4162 amp
* Spectro-Viz plus photometric accuracy is 13%, but standard curve calibration decreases the systematic error to
approximately equal the averaged precision (about 3 sign. figures), assuming the range of A is 0.1 to 1.0.
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Error Analysis Example

Error analysis is always a difficult area for students. However, the careful consideration of

experimental error is one of the important skills that we need to learn to be effective scientists. In

the following discussion, the errors in a titration experiment are considered. The first section is a

detailed look at how to determine the most important errors. The second section is an example of

the corresponding text that would be written in a lab report for CH141-142.

Determining the Important Errors

 The purpose of the error analysis section of the lab report is to determine the most important

errors and the effect that those errors have on the final result.

 Random Errors: Random errors cause positive and negative deviations from the average

value of a measurement. Random errors cancel by averaging, if the experiment is repeated many

times. Upon averaging many trials, random errors have an effect only on the precision of a

measurement. The effect of random errors is primarily on the precision. Every non-integer

experimental measurement is a source of random error. The random error is estimated from the

readability of the device. A table of typical measurements and the associated precision, under

practical circumstances, is given below. For instrument readings, to avoid round-off error, report

one extra significant figure and then underline the digit that is not significant.

Volumetric flasks and pipettes precision (relative) significant figures 10 mL (^)  0.03 mL 3 i.e. 10.0 mL 25 mL (^)  0.03 mL 3 25.0 mL 50 mL (^)  0.05 mL 3 50.0 mL 100 mL (^)  0.08 mL 4 100.0 mL Auto-pipettors 10 L  0.05 L (0.5%) 3 i.e. 10.0 L 100 L  0.3 L (0.3%) 3 100. L 1000 L  2 L (0.2%) 3 1000. L Analytical Balance 0.1000 g (^)  0.0001 g 4 e.g. 0.3456 g 1.0000 g (^)  0.0001 g 5 2.3456 g 10.0000 g (^)  0.0001 g 6 12.3456 g Spectrophotometer (Spectro-Viz*) 0.100  0.003 ( 3%) 2 e.g. 0. 0.500 (^)  0.003 ( 0.6%) 2 0. 1.000  0.004 ( 0.4%) 3 1. 1.500 (1 sign. fig. for A>2) (^)  0.015 ( 1%) 2 1. pH Meter 7.00 (^)  0.02 ~3 e.g. 6. Electronic Pressure Sensor 1.0 atm (760 torr) (^)  0.0005 atm ( 0.4 torr) 3-4 e.g 826.4 torr Constant Current Power Supply 0.400 amp (^)  0.0004 amp ( 0.1 %) 3 0.4162 amp

  • Spectro-Viz plus photometric accuracy is  13%, but standard curve calibration decreases the systematic error to approximately equal the averaged precision (about 3 sign. figures), assuming the range of A is 0.1 to 1.0.

 Systematic Errors: Without any changes in the procedure, systematic errors are repeated if

the experiment is repeated. Systematic errors have a biased effect on the final results; systematic

errors make the final result high or low, but not both. Instrument calibration errors are examples

of systematic errors. Environmental effects can also be causes of systematic error, for example a

change in lab temperature changing the calibration of a balance or the volume of a flask. An

example of a systematic error from the CaCO 3 precipitation experiment is that small particles

pass through the glass frits in a Gooch crucible, making the final precipitate mass too small.

Systematic errors affect the accuracy of the final results.

A given measurement can contribute to both random and systematic error. Non-integer

measurements always contribute to the random error. For example, a miscalibrated balance is a

source of random and systematic error. Systematic errors are often corrected by completing a

determination using a different method or by comparing results among different laboratories.

 Student Mistakes: Student mistakes are just student mistakes; they are neither random nor

systematic errors. Examples in this category are spills, misreading a device such as a burette,

misinterpretation of the procedure, incorrect handling of a micro-pipettor, and forgetting to rinse

out a beaker when doing a quantitative transfer. These errors are known and easily preventable,

if the experiment is repeated. Systematic errors occur with each repetition of the experiment,

assuming no changes in instrumentation. Mistakes should be noted in the Results section of your

report as mistakes.

Example: Titration of an Unknown Acid:

A 25.0-mL sample of an unknown acid is titrated with 15.67 mL of 0.1042 M NaOH. The

volume of the acid is determined using a volumetric pipette and the burette used in the

experiment has scale divisions every 0.1 mL. The standard base solution was made using an

analytical balance and a 100.0-mL volumetric flask. The end point is determined by visually

detecting the pink color of phenolphthalein.

Answer:

Random Measurement Errors: Every measurement is a source of random error. However, we

must identify those errors that have a significant effect on the final result. The effects on the final

result are determined using significant figure rules. The concentration of the unknown acid is:

Munknown = VtitrantMtitrant/Vunknown = 0.01567 L(0.1042 mol/L)/0.0250 L = 0.4821 M

Since only multiplications and divisions are involved, the number of significant figures in the

final result is equal to the smallest number of significant figures of the terms in the calculation.

We next discuss the errors associated with each term.

Volumetric Glassware and Analytical Balance Measurements: Large volume standard

volumetric glassware typically has a precision and accuracy of four significant figures. The

accuracy and precision of mass measurements on an analytical balance are also typically to four

significant figures (0.0001). The expected precision in the NaOH solution, using the analytical

balance and volumetric glassware, is four significant figures. The number of significant figures

in the 25.0-mL volumetric pipette is three. At best the final concentration is known to three

significant figures.

Measurements that are Interpolated between Scale Markings: The burette readings are not as

precise. To determine the volume of titrant delivered, two readings are made. Each reading is

recorded to the nearest 0.01 mL. However, visually estimating the volume to better than 0.