Higher Applications of Mathematics

Choosing suitable variables for a real-life situation, and recognising linear, quadratic, and exponential relationships.

Checking units are consistent, and working with absolute error, relative error, and tolerance.

Telling precision apart from accuracy, spotting implausible or over-extrapolated claims, suggesting improvements to a model, and using software well.

Using tree diagrams and Venn diagrams to work out the probability of combined events.

Categorical versus numerical data, why random sampling matters, and how to handle outliers.

Choosing the right diagram for a data type, and reading symmetry, normality, and skewness from a histogram.

Reading a scatter plot, interpreting a correlation coefficient, and the limits of using a linear model to predict.

The reasoning behind a hypothesis test, what a p-value means, and how to interpret a confidence interval.

Converting between interest rates of different frequencies, calculating present and future value, and valuing a whole series of payments.

How a loan repayment schedule splits into interest and capital, and how changes to a loan affect it.

Saving toward a specific goal, and the purpose and risk trade-offs of insurance products.

How banded tax rates work, and how inflation erodes the purchasing power of money over time.

Representing a project as an activity network, and finding the critical path that determines its overall length.

Reading a Gantt chart's floating activities, and using expected value to weigh up a risky decision.