Represent the distribution of multiple data sets for numerical variables using comparative representations; compare data distributions with consideration of centre, spread and shape, and the effect of outliers on these measures. Plan and conduct statistical investigations involving the collection and analysis of different kinds of data; report findings and discuss the strength of evidence to support any conclusions.
Two data sets are compared on three things: centre, spread and shape. An outlier moves some measures and barely touches others.
Method
Always compare all three
centre⋅spread⋅shape
One alone describes very little.
Outliers move the mean, not the median
The median is resistant. The mean is not.
Outliers hit the range hard
The range depends only on the extremes.
Use the same scale for both sets
Otherwise the comparison is meaningless.
Say how strong the evidence is
A small sample supports a weak conclusion at best.
Worked example
e.g.Class A: 6,7,7,8,9. Class B: 2,7,7,7,22. Compare them.
Find each mean.A:7,4B:9,0
Find each median.A:7B:7
Find each range.A:3B:20
Note which measure moved. The mean did; the median did not.22 is an outlier
Describe centre, spread and shape together.same median, far wider spread in B
State the evidence strength.n=5 each — too small for a firm conclusion
Practice
Compare centre, spread and shape. Then say how strong the evidence is.
1
Find the range of 4,9,6,15,8
Answer11
2
Which is resistant to outliers, mean or median?
AnswerThe median.
3
Two sets share a median but ranges are 3 and 30. Comment.
AnswerSame typical value, very different consistency.
4
Removing an outlier: which changes more, mean or range?
AnswerBoth change a lot; the median barely moves.
5
Why plot two sets on the same scale?
AnswerDifferent scales make the comparison meaningless.
6
You sampled 8 students. How strong is your conclusion?
AnswerWeak. Report it as tentative.
Next step
Practise Comparing Multiple Data Sets with instant marking
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