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