Graphs tools to measure and are helpful because you can easily show the result. In this chapter, we will look at some of the most important.

Histogram

The histogram is a helpful chart for displaying tendency, dispersion, and other information. You have your variable on the X-Axis and the frequency on the Y-Axis. Higher is the bar; higher is the frequency.

If you look at the image1, we have an example of a histogram for a new project’s estimation time (in the day). Our target is maxed 30 days, so by the graph, we can easily look at:

• The value dispersion by looking at where we have the bar. We have the most value between 27,5 and 35,83 days in this case. It becomes beneficial with a lot of observation (maybe 100, 1000);
• The cluster of value;
• The kind of distribution. Image1 – Histogram of working days need for estimate a new project

Pareto Chart

For this chart, look at the Pareto Analysis chapter.

Scatter Plot

The Scatter plot helps to look at a correlation of the two variable (X and Y).

If you look at the image2, you can three example:

• Negative correlation: when one variable gets a higher value, the other gets a lower value. In this case, you have all the points near an ideal line that start from a high value and go down;
• Positive correlation: when one variable gets a higher value, the other gets a higher value too. In this case, you have all the points near an ideal line that start from low weight and go down;
• No correlation: we have all the point dispersed around the graph.

Run Chart

This kind of chart signal a cycle trend or other trend that can occur in time. For instance, in the image3, we have a cycle that happens in months five and ten. It can be a signal of something wrong that we need to investigate.

Check Sheet

Like the run, the chart helps to signal something recurring. It’s a sheet where you write the occurrences of the events during the time. In the table1 for instance, you can quickly see that something occurs on Monday and Tuesday, which is a signal for future investigation.

Box and Whisker Plot

Box and whiskers are methods to look at value distribution about one or more variables. We have the data from the 25 and the 75 percentile in the box. The wicker is the outlier. In some cases, you can also have the median plotted as a horizontal line on each box. For instance, in image4, we look that most data (all from the 25 and the 75 percentile) of X1 are distributed in the range of 2 to 7, with a max value of ten and a min value of 2.