## Radar Charts

Radar charts are useful when you want to look at several
different factors all related to one item. Radar charts have
multiple axes along which data can be plotted. For example, you
could use a radar chart to compile data about a wide receiver on
a professional football team. On one axis, you could plot the
percentage of passes caught. Another axis would show his yards
per completion; another, his completions per 100 plays; another,
blocks made; and a final axis might show his interceptions.

If a team did this for all their wide receivers, they could
easily spot the best player as well as each player's strengths
and weaknesses.

In a radar chart, a point close to the center on any axis
indicates a low value. A point near the edge is a high value. In
the football example, we would high marks near the outside due to
the nature of what was being measured. In other scenarios, you
might want points near the center, or low values. When you're
interpreting a radar chart, check each axis as well as the
overall shape to see how well it fits your goals.

#### Radar chart
statistics:

For the radar chart, the following statistics are
calculated:

**Mean:** |
the average of all the values in the
series. |

**Maximum:** |
the maximum value in the
series. |

**Minimum** |
the minimum value in the
series. |

**Sample Size** |
the number of values in the
series. |

**Range** |
the maximum value minus the minimum
value. |

**Standard Deviation** |
Indicates how widely data is spread
around the mean |

Create Radar Charts using PathMaker's Data Analyst tool.