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Notes on our Data Techniques

Below we try and highlight why we do what we do. 

If you want something different or have other recommendations please contact us. 

We also provide custom dashboards if desired.

Choosing Average (Mean) vs Median

As we began to build dashboards we tried to understand what would be critical to getting the fullest picture. Understanding a baseline or average to various counties and topics is critical. Except there can be severe skews in the data causing the Average KPI to be a poor indicator. We often check our data sets for distribution patterns when we build it. Some examples below.

Average -  a number that is calculated by adding quantities together and dividing the total by the number of quantities 

Median - The median is the value that’s exactly in the middle of a dataset when it is ordered. It’s a measure of central tendency that separates the lowest 50% from the highest 50% of values.

In skewed distributions, the median is the best measure because it is unaffected by extreme outliers or non-symmetric distributions of scores

Cash Rents Skew.JPG

Distribution of Cash Rent on a national level (Above). Notice the positive skew

Farm Skew.JPG

Example of skewed data when comparing average size farm. Extra large farms skew the data affecting the average

Corn Yields from a national data set. Overall nationally Corn yields show a normal distribution. Here the average and the median are almost identical. 

Corn Yield normal distribution.JPG
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