Statistics

New Zealand

Level 4

Lesson

Statistics are used to justify many points of views. Once a scientific study has shown a particular conclusion using statistics, news articles often repeat these studies as "proof" of a certain conclusion, as though it were now a scientific fact. However, there are many different ways to collect data in a scientific study, some of which may not be appropriate to "prove" a certain conclusion.

A 2011 study of 11,000 children in Britain found that those children who spent a lot of time watching TV when they were 5 years old were more likely to have behavioural problems when they were 7 years old, but that this was not true for playing video games.

Some media outlets took this as "proof" that video games do not have any negative effect on young children. For example, gaming website IGN published an article with the title "Games definitely don't harm kids, says huge study". However, this study in fact only showed that children who played games when they were 5 years old were not *worse* behaved when they were 7 years old, as is discussed in the Sydney Morning Herald article "Video games are good for kids. Really?"*. *Have a read of these two articles for yourself, and have a go at answering the following questions:

- Read the first section (the summary, called the "Abstract"). What are your first thoughts?
- How was the study data collected?
- Are there any problems with the way the data was collected?
- What does the IGN article suggest about the impact of playing video games on kids?
- Why does the Sydney Morning Herald article disagree with the IGN article?
- Are you convinced that the study proves that video games have no negative effect on children?
- Try to design your own experiment to collect data about the effect of video games on children. What would you measure, and how would you measure it?

Plan and conduct investigations using the statistical enquiry cycle:– determining appropriate variables and data collection methods;– gathering, sorting, and displaying multivariate category, measurement, and time-series data to detect patterns, variations, relationships, and trends;– comparing distributions visually;– communicating findings, using appropriate displays.