I will answer your question in a couple of ways.
First as a concept:
Kurtosis is a measure of whether the data are peaked or flat relative to a normal distribution. That is, data sets with high kurtosis tend to have a distinct peak near the mean, decline rather rapidly, and have heavy tails. Data sets with low kurtosis tend to have a flat top near the mean rather than a sharp peak. A uniform distribution would be the extreme case.
Now as a mathematical formula:
For univariate data Y1, Y2, ..., YN, the formula for kurtosis is:
where is the mean, is the standard deviation, and N is the number of data points.
You may find more information at this website:
http://www.itl.nist.gov/div898/handbook/eda/section3/eda35b.htm