Students:

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

• collect categorical and numerical data through observation or by conducting surveys, eg observe the number of a particular type of insect in one square metre of the playground over time

Construct displays, including column graphs, dot plots and tables, appropriate for data type, with and without the use of digital technologies (ACMSP119)

• tabulate collected data, including numerical data, with and without the use of digital technologies such as spreadsheets [ICT]

• construct column and line graphs of numerical data using a scale of many-to-one correspondence, with and without the use of digital technologies

  • name and label the horizontal and vertical axes when constructing graphs (Communicating) [Literacy]

  • choose an appropriate title to describe the data represented in a data display (Communicating) [literacy]

  • determine an appropriate scale of many-to-one correspondence to represent the data in a data display (Reasoning)

  • mark equal spaces on the axes when constructing graphs, and use the scale to label the markers (Communicating) [Literacy]

• construct dot plots for numerical data, eg the number of siblings of each student in the class [ICT]

• consider the data type to determine and draw the most appropriate display(s), such as column graphs, dot plots and line graphs

  • discuss and justify the choice of data display used (Communicating, Reasoning) [Critical and creative thinking]

  • recognise which types of data display are most appropriate to represent categorical data (Communicating)

Describe and interpret different data sets in context (ACMSP120)

• describe and interpret information presented in tables, dot plots, column graphs and line graphs, eg 'The graph shows that the heights of all children in the class are between 125 cm and 154 cm)' [Literacy]

  • determine the total number of data values represented in tables, dot plots and column graphs, eg find the number of students in the class from a display representing the heights of all children in the class (Problem Solving, Reasoning) [Numeracy]

  • identify and describe relationships that can be observed in data displays, eg ‘There are four times as many children in Year 5 whose favourite food is noodles compared to children whose favourite food is chicken' (Communicating, Reasoning) [Literacy]

Dot plots are an alternative to a column graph when there are very few data values. Each value is recorded as a dot so that the frequencies for each of the values can be counted easily.

Categorical data can be separated into distinct groups, eg colour, gender, blood type. Numerical data is expressed as numbers and obtained by counting, or by measurement of a physical attribute, eg the number of students in a class (count) or the heights of students in a class (measurement).

Data selected for interpretation can include: census data, environmental audits of resources such as water and energy, and sports statistics.

Students:

Interpret and compare a range of data displays, including side-by-side column graphs for two categorical variables (ACMSP147)

• interpret data presented in two-way tables [Literacy]

• create a two-way table to organise data involving two categorical variables, eg:
  

• interpret and compare different displays of the same data set to determine the most appropriate display for the data set

  • compare the effectiveness of different student-created data displays (Communicating)

  • discuss the advantages and disadvantages of different representations of the same data (Communicating) [Critical and creative thinking, Ethical understanding]

  • explain which display is the most appropriate for interpretation of a particular data set (Communicating, Reasoning) [Literacy, Critical and creative thinking]

  • compare representations of the same data set in a side-by-side column graph and in a two-way table (Reasoning)

Data selected for interpretation can include: census data, environmental audits of resources such as water and energy, and sports statistics.

Also refer to the 'Introduction' tab.

Also refer to language in Data 1.