Expectations
What are the expectations for data analysis for the year I teach?
The following table summarises the position of the draft Australian curriculum: mathematics with regard to teaching of statistics (data) for years 1-7.
Continuum of data representation skills
|
Year |
Expectations |
|
1 |
Use or construct simple pictographs Identify links between lists, tables and pictographs |
|
2 |
Use tallying to record data and construct tables, pictographs and bar and column graphs Use lists, tables and graphs of simple data to attempt to interpret and explain Identify that information remains the same even though representations may change |
|
3 |
Make predictions, carry out investigations about familiar situations to gather data and report the results Make and use tables, diagrams and graphs, including dot plots that have prepared baselines, and identify the links between them Understand the importance of scale and equally spaced intervals on an axis |
|
4 |
Generate questions and use surveys to obtain data and use the results (including the use of ICT) to answer questions Use ICT while constructing, reading, interpreting and identifying links between tables and simple graphs that contain more complex relationships between data and symbols Identify how a small sample size impacts on outcomes of data compared to larger numbers in trials of chance events using ICT |
|
5 |
Collect data over time to carry out an investigation into the relationship between variables, report results draw conclusions and justify them Begin to explore bivariate data over time (for example, identify that comparison of the growth of pea and bean plants over several weeks requires that points be plotted on identical axes) Use lists and dot plots to identify the mode and median Analyse and compare a range of data representations for specific situations |
|
6 |
Construct, read and interpret tables and graphs including ordered stem and leaf plots, and construct pie charts and other simple data displays including using technology Analyse data in the media and elsewhere for misleading representations that may result from sampling a population Use repeated measurements to explore variation and error |
|
7 |
Use ICT and compare data sets using mean, median, and range and show reasoning Collect univariate and simple bivariate data and use of back-to-back stem plots and scatter plots to investigate questions |
An in depth discussion of The Development of Graph Understanding in the Mathematics Curriculum can be found on this NSW DET link. Not only does this link provide information on the history and background of graphing, the role of technology, the development of graph interpretation and creation but it also gives excellent examples of types of graphs and their relationships.
For years 3-6 the draft Australian curriculum: mathematics suggests:
‘These years focus on the importance of students studying coherent, meaningful and purposeful mathematics that is relevant to their lives. Students still require active experiences that allow them to construct key mathematical ideas, but there is a trend to move to using models, pictures and symbols to represent these ideas.’
This strongly implies that the approach of MyScience aligns closely with the curriculum intentions of dealing with real, meaningful data and using graphical methods to represent and interpret the data.
MyScience investigations provide an authentic context for the collection of data to address the demands of the year 5 and 6 draft Australian curriculum: mathematics. MyScience students are usually performing ‘fair test’ investigations looking at the effect of one variable (independent) on another variable (dependent). For example, students may investigate the effect of light on the preferred hiding spots of slaters. They may set up a shoe box containing slaters that has a well-lit area and a dark area. The setting up of light and dark places provides the independent variable, and the counting of the numbers of slaters at each location is the dependent variable. Data obtained by this type of investigation is called bivariate data. If you want to learn more about univariate and bivariate data, it is concisely summarised in a table at this link. Univariate data is based on data that describes, such as the number of students in year 5 at a particular school. Bivariate data is data that tends to explore relationships and cause-and-effect. Note that this draft Australian curriculum: mathematics indicates that by year 5 students should begin to explore bivariate data that has been collected over time. This is a simple example of bivariate data. The independent variable (the one that is deliberately changed) is actually time and the dependent variable is measured to give the result. An example might be describing the growth of a plant in terms of its change of height over time. This activity is descriptive over time but does not constitute a fair test. A MyScience investigation might look at the effect of fertiliser on growth of plants. Now the independent variable becomes use of fertiliser and the dependent remains the height of the plants. This is an investigation based on the collection of bivariate data, but in addition, students will often collect their data over time to get a better understanding of when in the growth of plants that the fertiliser may have the greatest effect. Graphing such results would involve putting time on the horizontal axis, height of plants on the vertical axis and two sets of data plotted and joined by lines to represent the plants grown with fertiliser and those grown without.
In primary school, it is expected that students will have dealt with data collected around one variable (univariate) for example, the height of students in the class, the age of students at a school and processed it. Data representations include pictographs, bar and column graphs, ordered leaf and stem plots and dot plots. In a MyScience investigation the data is likely to be bivariate and represented as bar, column, scatter plots or line graphs.