11–12Mathematics Standard 11–12 Syllabus (2024)
The new Mathematics Standard 11–12 Syllabus (2024) is to be implemented from 2026 and will replace the Mathematics Standard Stage 6 Syllabus (2017).
2026, Term 1
- Start teaching the new syllabus for Year 11
- Start implementing the 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 the new syllabus for Year 12
- Start implementing the new Year 12 school-based assessment requirements
2027
- First HSC examination for the 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 Loading and Loading and explain when each is needed
Explain the difference between Loading that show Loading and those that have a Loading relationship
Identify the Loading and Loading within a bivariate Loading where appropriate
Analyse relationships between independent and dependent variables that may be described as causal
Represent a bivariate dataset using a Loading
Create a Loading 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 Loading between two variables
Describe the strength of a Loading between two variables as strong, moderate or weak, and its direction as positive or negative
Determine and interpret the Loading and Loading of the line of best fit from a given Loading to form an Loading of the line
- Calculate and interpret Pearson’s correlation coefficient () for a bivariate dataset using a scientific calculator to quantify the strength of a linear association between the two variables
Determine the equation of the Loading 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 Loading and Loading for bivariate datasets within a variety of contexts