Plotting Data with Box and Whisker Charts

The Box-Plot or Box-and-Whiskers-Diagram is a convenient way of graphically depicting groups of numerical data through their quartiles. A Box and Whisker chart shows distribution of data into quartiles, highlighting the mean and outliers. The boxes may have lines extending vertically called whiskers. These lines indicate variability outside the upper and lower quartiles, and any point outside those lines or whiskers is considered an outlier.

In the KS6800A PathWave Measurement Analytics software, the Box and Whisker charts cannot be plotted by default for any measurement data. To view measurements using Box and Whisker charts, you must first plot Histogram charts for integer and float data types.

Converting Histogram Charts to Box and Whisker

To convert a Histogram chart (plotted by default for integer or float data types) to a Box and Whisker chart:

  1. Click to select the Histogram chart that you wish to convert to Box and Whisker.

  1. Click to view the Select Chart Type menu.

  1. Select Box and Whisker to plot the corresponding chart.
The Box and Whisker chart for the plotted data appears. Note that the Select Chart Type menu icon changes, indicating that Box and Whisker chart has been plotted. Also, the baseline is removed for all chart types other than Histogram.
  1. Hover the cursor over the chart to view the values. This chart displays the minimum, lower centroid (one standard deviation below the mean), the median, upper centroid (one standard deviation above the mean), and the maximum values of the measurement. The corresponding values are displayed in the format: min: <minimum value>, q1: <lower quartile value>, median: <mean value>, q3: <upper quartile value>, max: <maximum value>.
The graph below displays vertical distribution of the measurement counts, which means that the X-axis now represents the total number of measurements and the Y-axis now shows the range of measurement values obtained. The red-dashed lines that indicate the limits (if defined) are displayed on the horizontal scale in this case.

In the example shown above, the corresponding data can be easily interpreted in the format explained above.
  1. Click to close the window for the displayed chart.