One of the more challenging parts of using real data to teach statistics is the difficulty in finding data sets that are accessible for your students, and then wrangling the data into a form that is useable within the available software. One of the many things that the free stats software “R” has going for it is a large bank of pre-installed demo datasets that can be easily accessed and manipulated.
Once R is installed, to find out about the available data sets simply type the command data() and a window will appear with a complete list and a short description of teach. Typing the name of one of the data sets and hitting enter will display it in all its glory.
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)
Once you have a sense of the datasets themselves, they can be very useful starting points for classroom activities and investigation. In this blog I will describe an easy way to get started with the “faithful” data set, which contains the duration of, and time between, eruptions of the Old Faithful geyser in Yellowstone National Park. Setting a homework to learn about Old Faithful in advance of the lesson may help students to familiarise themselves with the context before being asked to think about the data in detail.
So, now you have some data – what can be done? Get students to suggest a starting point; perhaps a graph of some kind would be useful? Try typing plot(faithful)
![](data:image/png;base64,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)
R automatically decides the most appropriate graph for the data. In this case, as the data is bivariate, it defaults to a scatter graph. Ask students: what does the graph appear to show? Are there any obvious features? The eagle-eyed may spot that although there is some sense of a positive correlation, actually, there appear to be two sub-populations each with little or no correlation.
Challenge your students to suggest a possible explanation for this. Why might some be shorter and some be longer? They may notice that the longer duration eruptions appear to coincide with a longer waiting time between eruptions.
Ask students how they might choose to investigate further and try creating graphs of their suggestions, perhaps plot just the waiting times – plot(faithful$waiting, type = “h”) or just the eruption lengths – plot(faithful$eruptions, type = “h”). Adding the $ sign allows you to specify a named column from the data set and ignore the rest, adding type = “h” tells R to draw a line chart instead of plotting individual points.
Either of these groups shows a new pattern: the short and long durations appear to oscillate, so students can hypothesise that if there is a long eruption, it is likely the next one will happen sooner and be of shorter duration, or vice versa.
It can be difficult to see this pattern with all 272 data points, but using the head() command will allow you to select the first n rows as follows: plot(head(faithful$eruptions, n=20), type = “h”)
This is almost the same as before but head(faithful$eruptions, n=20) has simply replaced faithful$eruptions to give control over the amount of data plotted. Try changing the value of n to use more or less data.
![](data:image/png;base64,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)
The more students are able to examine data from different viewpoints, the more they will be able to spot features of data, suggest explanations and create new avenues of investigation. The pre-installed data sets alongside quick and easy (when you know how) graphing capability in R can help you to lead discussion based lessons in which you can respond to student suggestions on the fly, rather than having to predict all their possible ideas in advance and prepare resources for them on more unwieldy software such as Excel.