11–12Mathematics Standard 11–12 Syllabus (2024)

Identify an issue and pose a question to a targeted Loading  to gather statistical information

Develop a survey by applying questionnaire design principles of clear language, unambiguous questions and consideration of number of choices

Examine issues of privacy, Loading , ethics and responsiveness to diverse groups and Loading 

Compare and contrast systematic sampling, self-selected sampling, random sampling and stratified sampling

Justify whether a Loading  obtained from a population is representative of the population by considering the sampling method

Describe the potential faults in the design and practicalities of a Loading  collection process by considering survey design, Loading  and observational studies, and misunderstandings and misrepresentations

Classify and describe Loading  as numerical or categorical

Describe a Loading  as Loading  or Loading 

Describe a Loading  as Loading  or Loading 

Identify collections of data that can be described as numerical or categorical depending on responses

Recognise and explain why some Loading  need to be grouped to allow for appropriate representation and analysis

Use a spreadsheet to organise and represent data using appropriate Loading 

Represent a numerical dataset as either a Loading  table or a Loading  distribution table and graph the associated histogram with polygon, both with and without using digital tools

Represent Loading  in tables and column graphs as appropriate, with and without using digital tools

Select the type of graph best suited to represent various single datasets and justify the choice of graph

Identify and describe the shape of the distribution of a dataset as either Loading , positively Loading  or negatively skewed

Interpret and analyse dot plots, line graphs, sector graphs, Loading , Loading  and divided bar charts related to real-world applications

Analyse a statistical Loading  and justify the choice of graphical representations used for the relevant dataset

Interpret and consider limitations of graphical representations to make conclusions and predictions

Explain why a given graphical representation can lead to a misinterpretation of data

Describe the Loading , Loading  and Loading  as Loading  and calculate their values for a dataset in graphical form and tabular form, using a scientific calculator and other digital tools

Identify and describe datasets as uniform, unimodal, bimodal or multimodal

Identify the Loading  and Loading  as Loading  to describe variation in a dataset

Compare datasets using measures of centre and measures of spread

Examine the merits of each measure of centre and justify where each measure is most appropriately used

Identify and describe real-world examples illustrating appropriate and inappropriate uses of measures of centre and measures of spread

Use a spreadsheet to analyse data including calculating measures of centre and spread

Determine the Loading  from a set of Loading  or graphical representation

Determine the Loading  of datasets

Compare and contrast the use of range and IQR as measures of spread

Represent numerical datasets using a Loading  to display a five-number summary, with and without using digital tools

Compare and contrast the measures of centre, spread and shape using Loading  box plots

Determine Loading  from datasets displayed in histograms and dot plots, and represent these datasets as a box plot

Interpret box plots to draw conclusions and make inferences about a dataset

Identify Loading , gaps and Loading  and explain their occurrence in the context of the data

Explain the impact of outliers on the measures of centre and spread