Data handling includes the collection, presentation, interpretation and evaluation of data from both primary and secondary sources. The quality of the data is extremely important when assessing the strengths and limitations of models and theories.Data must be accurate, reliable and repeatable if it is going to be used in this way. Scientists often present their findings through various kinds of visual representation. It is therefore important for students to develop their skills so they can both organise and interpret data from visual representations, including tables and graphs.​After working through this topic, you will be able to:understand why it is important to teach students how to handle data;appreciate some of the difficulties students have when working with data; andhave a range of teaching strategies to support the development of data handling skills.