Key skills aimed to be developed included formulating statistical questions, measuring and collecting data, using CODAP (https://codap.concord.org/) to organize and visualize data using dot plots, describing data distributions and their characteristics, such as arithmetic mean, mode and range, interpreting data and drawing conclusions from data. The project took up approximately 27 class periods (each 40 minutes) over ten weeks.

The weather-related data were gathered from the national meteorology office website and the other data were collected by the students using questionnaires that they developed. Based on the national mathematics curriculum students have had prior experience with formulating investigation questions, collecting, visualizing and interpreting categorical data as well as calculating the average. Nevertheless, the first two pilot projects indicated the need for considering (1) the notion of distribution as an aggregate group of data values, (2) dot plot representation to visualize distribution shape and two categorical variables (in the curriculum they learn only bar graphs or pie charts), (3) different types of statistical questions, such as summary, comparative and relationship questions, and (4) a trial activity for exploring how to use CODAP to organize and analyze data before the actual project.

The students were confident to use ICT tools but they have not used any data analysis software, such as CODAP, to explore data before. Thus, there was a CODAP trial activity early in the sequence of tasks involved in the project to introduce how to use CODAP tools to organize and analyze data after three lessons on features and types of statistical questions. During this activity students explored students’ reaction times by collecting data in the class. It was during this activity that students were introduced to dot plots, which is not used in the national curriculum, and encouraged to think about distributions and their characteristics, such as shape, center and spread/variability, rather than only to focus on calculating statistics without really understanding what they mean when interpreting results. This activity also demonstrated how to use the DA cycle in a statistical investigation.