11 Broken Chair Lawsuit by HC120612185140


									Title: Broken Chair Lawsuit

Topic: Variation of Data

Objective: Use the normal curve and standard deviation as a measure of variability to make
decisions about data.

State Core Reference: _________________________________________________________



An average woman weighs about 150 lbs with a standard deviation of 30 lbs. A woman
weighing 350 lbs goes into a fast food restaurant to get her meal, sits down and the seat
collapses. She falls and while not seriously hurt, proceeds to sue the business for a couple of
million for pain, suffering and embarrassment because the chairs did not support her weight.

Normal Distribution:

When graphed, the distribution of many measurements approximate the normal curve, such as
human height and human IQ data, and follow the 68%-95%-99.7% rule.


Students take either the role of the prosecuting or defense attorney and make an argument for
their case using statistics. Ask students to hand in a paragraph that would represent the closing
remarks of the attorney.


Allow students to present their arguments. Arguments may include:

Defendant: Most students will say that the 350 lb woman was an extreme outlier, one that the
fast food business shouldn't have to consider. In this case, the woman’s weight is almost 7
standard deviations from the mean on a normal curve.

Prosecutor: Issues may include asking where do we draw the line and doesn't a food service
business have a duty to provide for everyone, shouldn't they at least have a sign saying the
maximum capacity of a chair, usually around 250-300 lbs.


                                 Statistics is FUNdamental – 2008
1) One fast food business claims that it serves 47 million people every day. How many would
be served in a year? How should this information influence the arguments made by the
prosecutor or defendant?

2) Using means and standard deviations to measure variability carries the assumption that the
distribution of human weights is normal. Is this a safe assumption? What would be an
alternative measure of variability for this statistic?

Notes to Self

                                Statistics is FUNdamental – 2008

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