Processing Uncertainties in Chemistry
What is uncertainty?
- Uncertainty is quantitative indication of the quality of the result
- It is the difference between the actual reading taken (caused by the equipment or techniques used) and the true value
- It is a range of values around a measurement within which the true value is expected to lie and is an estimate
- Uncertainties are not the same as errors
- Errors arise from equipment or practical techniques that cause a reading to be different from the true value
- Uncertainties in measurements are recorded as a range (±) to an appropriate level of precision
Table showing different uncertainties
Uncertainty | |
in a reading | ± half the smallest division |
in a measurement | at least ±1 smallest division |
in repeated data | half the range i.e. ± ½ (largest - smallest value) |
in digital readings | ± the last significant digit (unless otherwise quoted) |
Types of uncertainty
- Uncertainty is grouped into three main types:
-
Absolute uncertainty
- The actual amount by which the quantity is uncertain
- e.g.if v = 5.0 ± 0.1 cm, the absolute uncertainty in v is 0.1 cm
-
Fractional uncertainty
- The absolute uncertainty divided by the quantity itself
- e.g.if v = 5.0 ± 0.1 cm, the fractional uncertainty in v is =
-
Percentage uncertainty
- The ratio of the expanded uncertainty to the measured quantity on a scale relative to 100%
- This is calculated using the following formula:
-
Percentage uncertainty =
How to calculate absolute, fractional and percentage uncertainty
The key pieces of information from this burette reading are the smallest division and the reading
- The uncertainties in this reading are:
- Absolute
- Uncertainty = = 0.05 cm3
- Reading = 19.6 ± 0.05 cm3
- Fractional
- Uncertainty = = = cm3
- Percentage
- Uncertainty = = = 0.5%
- Reading = 19.6 ± 0.5% cm3
- Absolute
Propagating uncertainties in processed data
- Uncertainty propagates in different ways depending on the type of calculation involved
Adding or subtracting measurements
- When you are adding or subtracting two measurements then you add together the absolute measurement uncertainties
- For example,
- Using a balance to measure the initial and final mass of a container
- Using a thermometer for the measurement of the temperature at the start and the end
- Using a burette to find the initial reading and final reading
- In all of these examples, you have to read the instrument twice to obtain the quantity
- If each time you read the instrument the measurement is 'out' by the stated uncertainty, then your final quantity is potentially 'out' by twice the uncertainty
Multiplying or dividing measurements
- When you multiply or divide experimental measurements then you add together the percentage uncertainties
- You can then calculate the absolute uncertainty from the sum of the percentage uncertainties
Exponential measurements (HL only)
- When experimental measurements are raised to a power, you multiply the fractional or percentage uncertainty by the power
The coefficient of determination, R2
- The coefficient of determination is a measure of fit that can be applied to lines and curves on graphs
- The coefficient of determination is written as R2
- It is used to evaluate the fit of a trend line / curve:
- R2 = 0
- The dependent variable cannot be predicted from the independent variable.
- R² is usually greater than or equal to zero
- R2 between 0 and 1
- The dependent variable can be predicted from the independent variable, although the degree of success depends on the value of R2
- The closer to 1, the better the fit of the trend line / curve
- R2 = 1
- The dependent variable can be predicted from the independent variable
- The trend line / curve is perfect
- Note: This does not guarantee that the trend line / curve is a good model for the relationship between the dependent and independent variables
- R2 = 0