11–12Mathematics Standard 11–12 Syllabus
The new Mathematics Standard 11–12 Syllabus (2024) is to be implemented from 2026.
2025
- Plan and prepare to teach the new syllabus
2026, Term 1
- Start teaching new syllabus for Year 11
- Start implementing new Year 11 school-based assessment requirements
- Continue to teach the Mathematics Standard Stage 6 Syllabus (2017) for Year 12
2026, Term 4
- Start teaching new syllabus for Year 12
- Start implementing new Year 12 school-based assessment requirements
2027
- First HSC examination for new syllabus
Content
Year 12 – Standard 2
- MAO-WM-01
develops understanding and fluency in mathematics through exploring and connecting mathematical concepts, choosing and applying mathematical techniques to solve problems, and communicating their thinking and reasoning coherently and clearly
- MST-12-S2-08
analyses bivariate datasets using statistical processes
Distinguish between situations involving one variable data and bivariate data and explain when each is needed
Explain the difference between variables that show correlation and those that have a causal relationship
Identify the independent and dependent variables within a bivariate dataset where appropriate
Analyse relationships between independent and dependent variables that may be described as causal
Represent a bivariate dataset using a scatter plot
Create a line of best fit on a scatter plot for a bivariate dataset, by eye and with digital tools
Describe the form of a dataset as linear or non-linear based on the association between two variables
Describe the strength of a linear relationship between two variables as strong, moderate or weak, and its direction as positive or negative
Determine and interpret the intercept and gradient of the line of best fit from a given graph to form an equation of the line
Determine the equation of the least-squares regression line for a bivariate dataset using a scientific calculator
Use a spreadsheet to construct a scatter plot and the least-squares regression line for a bivariate dataset
Examine lines of best fit to make predictions and recognise limitations of interpolation and extrapolation for bivariate datasets within a variety of contexts