# Environmental Factors Affecting Where People Geocache
## 3 Data Analysis  
The number of caches per zone followed a power law distribution, with 2234 of the 4403 zones only having one cache. Similarly, the number of logs per cache in zones also followed a power law distribution, with 1959 zones averaging 1 find or fewer per cache.  
We divided the zones into low- and high-cache zones and into low- and high-log zones. Low-cache zones had only one cache, while high-cache zones had more than one. Low-log zones averaged one log or fewer per cache, while high-log zones averaged more than one log per cache. This rough division allowed us to study what attributes corresponded to zones in each category.  
We compared the values for different attributes between the high and low groups using a two-tailed Student's \(t\)-test in R. All significance values below are for \(p<0.05\). In addition, we confirmed results in both directions in the data. For example, if high-cache zones show a higher average for variable \(X\) than low-cache zones, then we confirmed that areas with a higher average for variable \(X\) indeed have a higher average number of caches. Below, we will only report the results in one direction for clarity, but the significance holds in both directions unless otherwise noted.  
Note that all demographic features describe the _zones_, not necessarily the users who hid or found the caches.  
The low- and high-cache zones shed insight into where people _hide_ caches. We found that, among all the demographic data we collected, the only statistically significant difference between low- and high-cache zones was the population density. Low-cache zones had significantly higher population density _vs._ high-cache zones (717 people/km\({}^{2}\)_vs._ 576 people/km\({}^{2}\)). That is, caches are more often hidden in places with lower density.  
However, looking at the number of logs per zone paints an entirely different picture. First, the population density result from the low- and high-cache zones was reversed. While high-cache zones have lower population density, high-log zones have higher population-density than low-log zones (778 people/km\({}^{2}\)_vs._ 485 people/km\({}^{2}\)). This means people are logging more searches in higher-density areas.  
Many other demographic attributes were significant as well:  
Age: High-log zones have significantly younger populations (37.9 _vs._ 39.9 years old on average).  
Climate: High-log zones were significantly warmer (averaging about 3 \({}^{\circ}\)F warmer than the measurements for low-log zones) and had less precipitation (an average of 41.6 mm less per year).  
Area: High-log zones were significantly smaller than low-log zones (171 km\({}^{2}\)_vs._ 306 km\({}^{2}\)), indicating more uphanness in high-log zones.  
Education: The education score of the population was significantly higher in high-log zones (2.14 _vs._ 2.08).  
Income: Median income was higher in high-log zones _vs._ low-long zones (about $6,170 higher).  
Crime: Crime was significantly higher overall in the personal and property crime sub-categories in high-log zones _vs._ low-log zones. This is likely an indication that high-log zones tended to be more urban. There were no significant differences for overall crime and personal crime; higher crime areas had no significant difference in the number of logs compared to lower-crime areas.  
The analysis of these zones reveals that, while lower population density areas tend to have more caches, higher population density areas tend to have more logs per cache.  
Furthermore, while no demographic features significantly impacted the number of caches in a zone, nearly all of our demographic features showed significant differences based on the number of logs. Despite a very democratic placement of caches, those with the most activity tended to be in zones that were wealthier, better educated, younger, and more urban, and had better weather.