Bite-sized Measurements and Uncertainty Study Notes for IB Physics HL/SL
Key points
Quantity | Name | Symbol |
---|---|---|
Length | Meter | m |
Mass | Kilogram | kg |
Time | Second | s |
Electric Current | Ampere | A |
Thermodynamic Temperature | Kelvin | K |
Amount of Substance | Mole | mol |
Power | Prefix | Symbol |
---|---|---|
10-12 | Pico- | p |
10-9 | Nano- | n |
10-6 | Micro- | µ |
10-3 | Milli- | m |
10-2 | Centi- | c |
103 | Kilo- | k |
106 | Mega- | M |
109 | Giga- | G |
The number of digits used to express a number carries information about how precisely the number is known
For some values, a number should be more precise (more significant figures), and for others, a number should be less precise (less significant figures)
How many significant figures are used in IB Physics? If not specified, always give your answer on IB exams to 3 significant figures.
There are certain rules which need to be followed to measure the significant figures of a number
A nice trick to help is the Pacific-Atlantic Rule:
What is systematic error in physics? A systematic error is a type of error that affects the accuracy of data collected in an experiment.
Systematic errors displace data measurements from their true value in the same direction and by the same magnitude; for example, all the measurements may all be too large or too small.
In the bulls eye example to the right, all of the data points are skewed to the left, where they are supposed to be at the center.
Systematic errors are commonly associated with set-up error such as improper calibration. A common example may be:
Frequently Asked Questions
Random error is revealed when repeated measurements of the same quantity show a spread of values, some too large some too small. The independent data values differ in both magnitude and direction from the mean.
In the bullseye example to the right, the data points are scattered from the mean, which would be somewhere in the middle.
Random errors are commonly associated with environmental changes and measuring procedures. Examples:
Frequently Asked Questions
Measurement accuracy refers to how close the data collected is to an accepted value. The accuracy of measurement is dependent on the presence of systematic error.
Measurement precision refers to how close the data points collected are to each other. This is dependent on random error between trials.
Bullseye example:
Frequently Asked Questions
Key points
Absolute Uncertainty is the uncertainty in a measurement, which is represented in the relevant units
Fractional Uncertainty is the Absolute Uncertainty divided by the standard quantity itself
Percent Uncertainty is the Absolute Uncertainty divided by the measurement, times 100%
Key points
Uncertainty is often represented through error bars in graphs.
The Minimum and Maximum lines are part of the line of best fit. They are found for linear lines
Key points
Multiplying a Scalar value and a Vector
Key point
Adding is much like adding numbers, numerically speaking.
Key points
Subtracting vectors is represented graphically as the shortest distance traveled from one end of a vector to another end of a vector
There are steps that can help with subtracting vectors
Key points
The Vertical Component is the component with respect to the y-axis.
The Horizontal Component is the component with respect to the x-axis.
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