Data Classification and Visualisation

statisticsandprobability core

Data classification and visualisation | NSW Curriculum Website

• MA4-DAT-C-01 classifies and displays data using a variety of graphical representations

📖 Prior Knowledge

Content	Prior knowledge	Used for
Represents Numbers B	- number lines	- axis scales
Data B	- column graphs	- histograms
Fractions Decimals Percentages	- fraction of a quantity, proportions	- interpreting sector and bar graphs

Classify data as either numerical (discrete or continuous) or categorical (nominal or ordinal) variables.pdf

• Define a variable in the context of statistics as any characteristic, number or quantity that can be measured or counted
• Classify and describe variables as numerical or categorical
• Describe a numerical variable as either discrete or continuous
• Describe a categorical variable as nominal or ordinal
• Distinguish between and compare numerical (discrete or continuous) and categorical (nominal or ordinal) variables

Display data using graphical representations relevant to the purpose of the data.pdf

• Represent single datasets using graphs, including frequency histograms and polygons, dot plots, stem-and-leaf plots, divided bar graphs, column graphs, line graphs, sector graphs and pictograms, with or without digital tools
• Include sources, titles, labels and scales when displaying data in a graph
• Select the type of graph best suited to represent various single datasets and justify the choice of graph
• Represent a dataset using a statistical infographic and justify the choice of graphical representation used

Interpret data in graphical representations.pdf

• Identify and interpret data displayed on graphs
• Identify features of graphical representations to draw conclusions
• Interpret patterns in graphical representations to make predictions
• Explain why a given graphical representation can lead to a misinterpretation of data