On
the
Side
Normal Distribution
Worksheets
Why
1.5?
FYI
Light
Bulbs and Dead Batteries
Java Applets
Many students are curious about the ‘1.5*IQR Rule’, i.e. why do we use Q1 - 1.5*IQR (or Q3 + 1.5*IQR) as the value for deciding if a data value is classified as an outlier? Paul Velleman, a statistician at Cornell University, was a student of John Tukey, who invented the boxplot and the 1.5*IQR Rule. When he asked Tukey, ‘Why 1.5?’, Tukey answered, ‘Because 1 is too small and 2 is too large.’
It has been shown that this is a reasonable rule for determining if a point is an outlier, for a variety of distributions. This worksheet asks the student to demonstrate this for the normal distribution.
Light Bulbs and Dead Batteries
Don Kerr, of Brisbane-based Zeno Educational Consultants, once told me that he believed that the lifetime of light bulbs and car batteries both have a decaying exponential distribution. I was intrigued by this, as every statistics textbook I have ever used always had a question that started, ‘Assume the lifetime of light bulbs is normally distributed, with mean....’. So I decided to ask my colleagues, which resulted in this interesting exchange.
Normal Approximation to the Binomial
A Java applet that visually demonstrates how accurately the normal distribution approximates the binomial distribution for given values of n and p.
| Read
Me First! | Introduction | Acknowledgements |
| Looking
for Patterns |Stemplots | Dotplots | Histograms |
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of Location | Measures of Spread |
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