Review the key concepts, formulae, and examples before starting your quiz.
🔑Concepts
Random Errors are caused by unpredictable fluctuations in environmental conditions or difficulties in reading instruments. They affect the precision of a measurement and cause data to scatter around a mean value.
Systematic Errors are caused by flawed experimental design or incorrectly calibrated instruments (e.g., zero offset error). They affect the accuracy of a measurement, shifting all readings in the same direction from the true value.
Precision refers to how close a series of measurements are to one another. High precision is indicated by a small range/standard deviation and relates to small random errors.
Accuracy refers to how close a measured value is to the accepted or 'true' value. High accuracy relates to small systematic errors.
To reduce Random Errors, one should take multiple repeat readings and calculate the mean value .
To eliminate Systematic Errors, instruments must be calibrated (zeroed) or the experimental technique must be adjusted. They cannot be reduced by repeating measurements.
On a linear graph, a systematic error is often indicated if the line of best fit does not pass through the origin when theory suggests it should.
📐Formulae
💡Examples
Problem 1:
A student measures the mass of an object as and its volume as . Calculate the density and its absolute uncertainty .
Solution:
- Calculate density: .
- Calculate fractional uncertainties: and .
- Sum fractional uncertainties: .
- Calculate absolute uncertainty: . Result: (rounded to appropriate significant figures).
Explanation:
Since density is calculated via division, we sum the fractional uncertainties of mass and volume to find the fractional uncertainty of the density.
Problem 2:
During a simple pendulum experiment, a student records the time for 20 oscillations as . If the formula for the period is , find the absolute uncertainty in the period .
Solution:
. Since is a constant (no uncertainty), the fractional uncertainty in is the same as in : . Result: .
Explanation:
When a value is divided by a constant, the absolute uncertainty is also divided by that same constant.