I was trying to find a ‘good’ real-life application of standard deviation when I stumbled across a site explaining the concept of volatility in share prices. Apparently, stock brokers often analyse the ‘volatility’ of a companies share price using standard deviation to measure the spread of the data around the mean.

I asked the students to find a company they like and note the previous 60 days share prices(sixty because it´s big enough to warrant putting the data in a grouped frequency table and small enough so that you´re not analysing data that is too far in the past). They then grouped the data in appropriate intervals and found the mean and standard deviation of the share prices. It was a nice way to see that companies that have a high share price volatility have a high measure for standard deviation. It also promoted great discussions on a number of different aspects of the process – namely the advantages and disadvnatges of grouping data into intervals.

The volatlity of the starbucks shares on the NASDAQ is shown below.

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