Examining the distribution of your data using histograms and normal QQ plots

The ESDA tools (refer to Exploratory Spatial Data Analysis) help you examine the distribution of your data.

When checking whether your data is normally distributed (close to a bell-shaped curve), the Histogram and Normal QQ Plots will help you. In the summary statistics provided by the Histogram, the mean and median will be similar, the skewness should be near zero, and the kurtosis should be near 3 if the data is normally distributed. If the data is highly skewed, you may choose to transform it to see if you can make it more normally distributed. Note that back transformation process generates approximately unbiased predictions with approximate kriging standard errors when you use Universal or Ordinary Kriging.

The Normal QQ plot provides a visual comparison of your dataset to a standard normal distribution, and you can investigate points that cause departures from a normal distribution by selecting them in the plot and examining their locations on a map. For an example, refer to Normal QQ and general QQ plots. Data transformations can also be used in the Normal QQ Plot.

Steps:

1. Click the point feature layer in the ArcMap table of contents that you want to examine.
2. Click the Geostatistical Analyst toolbar, point to Explore Data, then click either Histogram or Normal QQ Plot.

Tip:

In the Histogram, make sure that the Statistics box is checked to see summary statistics for the data.

Tip:

In the Normal QQ Plot, the points will fall close to the 45 degree reference line if the data is normally distributed.