Physics
Measurements and uncertainties
Measurements in physics
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Measurements in physics
Fundamental quantities and units
- Understand and recall the seven fundamental quantities used in the International System of Units (SI) – second, metre, kilogram, ampere, kelvin, mole, and candela.
- Be aware that each fundamental quantity has a associated SI unit: second for time, metre for length, kilogram for mass, ampere for electric current, kelvin for temperature, mole for number of particles, and candela for luminous intensity.
- Recognise that derived units are generated by combining the fundamental units, e.g. newtons for force (kg m/s²) or joules for energy (kg m²/s²).
Precision, Accuracy and Uncertainty
- Distinguish between precision (how closely individual measurements agree with each other) and accuracy (how close a measurement is to the true value).
- Understand that uncertainty represents a range within which the true value is likely to lie, and is sometimes described as the precision of the equipment.
- Reconstruct percentage uncertainty by dividing the absolute uncertainty by the measured value and multiplying by 100.
Measurement Techniques and Tools
- Differentiate between the types of measurements taken in an experiment, including discrete, continuous, and categorical measurements.
- Highlight the range of measuring tools, such as metre rules, vernier calipers, and micrometers, and their corresponding precisions.
- Grasp how random vs systematic errors can have different impacts on results and recognise ways to reduce these.
Significant Figures and Scientific Notation
- Implement the rules for counting significant figures in a given number.
- Round numbers according to the principles of significant figures, appreciating that uncertainties should have a maximum of two significant figures.
- Use scientific notation to conveniently express very large or small numbers.
Graphical Representation of Uncertainties
- Identify error bars on a graph as a basic visual indicator of the uncertainty of each datapoint.
- Understand how to calculate the gradient and its uncertainty of a line of best fit, incorporating uncertainties of individual measurements.
- Interpret the y-intercept of the best fitting line and its uncertainty.
Data Analysis
- Understand how to evaluate mean, median, and mode as statistical descriptors of a dataset.
- Recognise standard deviation as a measure of dispersion of a dataset.
- Perform propagation of uncertainties when doing calculations involving multiple measurements.
The aim is to understand and apply these principles and techniques to represent, analyse, and interpret scientific measurement data effectively in Physics.