- Describe and interpret different data sets in context (ACMSP120)
- Describe and interpret data presented in tables, dot plots, column graphs and line graphs.
- Pose questions and collect categorical or numerical data by observation or survey (ACMSP118)
- Pose and refine questions to construct a survey to obtain categorical and numerical data about a matter of interest
[S4 Single Variable Data Analysis]
- Investigate techniques for collecting data, including census, sampling and observation (ACMSP284)
- Recognise and explain the difference between a 'population' and a 'sample' selected from a population when collecting data
- Investigate and determine the differences between collecting data by observation, census and sampling
- Explore the practicalities and implications of obtaining data through sampling using a variety of investigative processes (ACMSP206)
- Investigate and question the selection of data used to support a particular viewpoint, e.g. the selective use of data in product advertising
- Explore the variation of means and proportions of random samples drawn from the same population (ACMSP293)
- Investigate ways in which different random samples may be drawn from the same population, e.g. random samples from a census may be chosen by gender, postcode, state, etc
[S5.1 Single Variable Data Analysis]
- Evaluate statistical reports in the media and other places by linking claims to displays, statistics and representative data (ACMSP253)
- Interpret media reports and advertising that quote various statistics, e.g. media ratings, house prices, sports results, environmental data
- Critically review claims linked to data displays in the media and elsewhere
[S5.2 Single Variable Data Analysis]
- Investigate reports of surveys in digital media and elsewhere for information on how data was obtained to estimate population means and medians (ACMSP227)
- Investigate survey data reported in the digital media and elsewhere to critically evaluate the reliability/validity of the source of the data and the usefulness of the data
- Make predictions from a sample that may apply to the whole population
[S5.2 Bivariate Data Analysis]
- Investigate a matter of interest, representing the dependent numerical variable against the independent variable, time, in an appropriate graphical form
- describe changes in the dependent variable over time, e.g. describe changes in carbon pollution over time