Getting busy with statistics

The screenshot you see is an example of the graphs you can output in my descriptive statistics Excel template without using any macros. I often find moving averages and boxplots / histograms to be extremely useful in analyzing raw data for stress and volume testing …

So what are my favourite descriptive statistics I like to analyse data with?

1. Box plots and histograms are great for displaying distribution and give you a good insight to characteristics of the data you are analyzing. A standard box-whisker chart plots up to 5 data sets using box-whisker symbols. Variants are box plots without the whiskers. The 5 data sets are sometimes called the maximum, 3rd quartile, median, 1st quartile and minimum, although they can represent any kind of quantities.
2. Trend line charts. A trend line is a straight line that fits a number of data points computed using linear regression (the least square method). This is excellent for predictive analysis of data, especially if you get roped into capacity planning activities. You do however need a signficant empirical baseline from which to draw your results, which usually means you have to execute many test runs in order to establish the data.
3. Good old line charts. A line chart with thinned results (for easier presentation) can give immediate insights to where your transaction response times went wrong. This is good for coarse analysis of rows of data. Some variations of the line chart is the moving average as provided by excel. I’m not sure on the accuracy of moving averages though. Can be useful when trying to smooth the curve.
4. In a spline charts, the data points are connected together using cardinal spline curves (as opposed to straight lines). The “tension” of the curve can normally be configured.