acquire, validate and represent data for nominal and ordinal categorical and discrete numerical variables, to address a question of interest or purpose using software including spreadsheets; discuss and report on data distributions in terms of highest frequency (mode) and shape, in the context of the data

How Bloomi helps with this

This is a NAPLAN-year topic. Bloomi teaches it with a short explainer, guided practice, and NAPLAN-style questions — every one traceable to this exact code.

What this looks like in the classroom

• recognising that ordinal data is a form of categorical data even though the data being collected might be numbers; for example, a rating scale using numbers \(1 – 5\) to represent the categories people can choose from when asked, “What rating would you give this film out of \(5\)?”
• determining the mode for a set of data and discussing that there may be more than one mode
• identifying the best methods of presenting data to illustrate the results of investigations and justifying the choice of representations