#StatisticsAndProbability #Core >[!info]- [Data classification and visualisation | NSW Curriculum Website](https://curriculum.nsw.edu.au/learning-areas/mathematics/mathematics-k-10-2022/content/stage-4/fa1961f47c) >- 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