This
problem gives students an insight into the fact that data can
be manipulated to give conflicting results and a glimpse of the
more difficult issues surrounding the study of statistics. It
contains a good mathematical problem solving element and draws
students into the workings of the Chi-squared test, resulting in a
greater understanding of the mechanics of the test.
Possible approach
Key to this task is the realisation that the Chi-squared test
requires grouping of data classes when individual classes contain
few elements and, in this case, that there are a variety of equally
sensible ways of grouping the data. Students might realise this
individually or this might emerge through classroom
discussion.
Key questions
Can you think of a convincing explanation for the expected
distribution of weights?
What choices are there to be made in a Chi-squared
calculation?
How would you group classes to most increase the Chi-squared
statistic?
Possible extension
If students have access to a spreadsheet, they might try to
invent their own set of data which exhibits this type of
behaviour.
Possible support
Rather than try to work out which would be the best grouping
before performing a calculation, suggest that different students
cluster the data categories individually and then perform the
standard Chi-squared test. The students could then compare results
and hopefully then realise that the grouping can significantly
affect the character of the result.