Review the key concepts, formulae, and examples before starting your quiz.
🔑Concepts
The independent variable is plotted on the -axis, while the dependent variable is plotted on the -axis.
A line of best fit (trend line) should be drawn to represent the mathematical relationship, which may be linear or a curve. It does not necessarily pass through all data points but should minimize the distance from them.
The gradient () of a linear graph is calculated using the change in divided by the change in , often represented as .
Interpolation is the process of estimating a value within the range of measured data points, whereas extrapolation involves extending the line of best fit beyond the experimental data range.
Error bars are used to represent the absolute uncertainty of the measurements on a graph. A line of best fit should ideally pass through all error bars.
To calculate the uncertainty in the gradient, lines of maximum and minimum slope (lines of worst fit) are drawn. These must still pass through all error bars.
Direct proportionality is indicated by a straight line passing through the origin , satisfying the equation .
Systematic errors can often be identified by a non-zero intercept on the -axis when the theoretical relationship predicts an intercept of zero.
📐Formulae
💡Examples
Problem 1:
A student measures the volume of a gas at different temperatures in Kelvin, keeping pressure constant. The resulting graph of against is a straight line. If the gradient of the graph is and the pressure is , determine the number of moles of the gas. (Use and note ).
Solution:
- From the Ideal Gas Law: .
- The gradient .
- Convert pressure to Pascals: .
- Convert gradient to : .
- Rearrange for : .
- .
Explanation:
The gradient of a vs graph represents according to Charles's Law and the Ideal Gas Equation. By substituting the known values into the gradient expression, the amount of substance can be calculated.
Problem 2:
A student determines the density of a liquid by plotting mass () on the -axis against volume () on the -axis. The best-fit line gradient is . The maximum possible gradient is and the minimum is . Calculate the density with its absolute uncertainty.
Solution:
- Density .
- Absolute uncertainty .
- Final value: .
Explanation:
The uncertainty in the gradient of a graph is found by taking half the difference between the steepest and shallowest possible lines of best fit that pass through the error bars.