Assignment 2

Z-Scores, Mean Center, and Standard Distance

 

 

    In assignment two we are looking at disorderly conducts in Eau Claire Wisconsin, mainly geared towards the hopping bar scene on Water Street area. I was given the addresses of all Disorderly Conduct violations around the city of Eau Claire in 2003 and 2009. Along with the violations and addresses, I was also given the number of arrests at each particular address. Although I was not given the reasons for these crimes, most related to fights and loud music, I still was able to analyze them spatially. I am interested in seeing how these patterns have changed over time. I was also given the addresses of bars in 2009, looking at the bars I want to see how many arrests took place at these addresses. The main question here, are the complaints coming from citizens warranted?

    Part 2

    In part two of the assignment we are looking at the mean centers and the weighted mean centers. The first process of completing this task was to upload the disorderly conduct arrests from 2003 around Eau Claire. By using the mean center tool in arctoolbox, I am able to quickly find the mean center for these arrests in 2003. Upon finding the mean center, I next wanted to find the weighted mean center for 2003 arrests. This tool was also in the arctoolbox, but for the weighted field I chose count. This would show the number of arrests at the given addresses. When building the map for 2003 I also used a graduated symbols map with natural breaks on the map allowing for me to be able to show the different number arrests for a given location.

    After finding the mean center and weighted mean center for 2003, I turned my focus towards 2009. Since I already found the mean center and weighted mean center in 2003 I was able to quickly compute these for 2009. Right now I have two maps, one for 2003 and one for 2009 for arrests from those years with the mean and weighted mean centers. For my third map I combined all of this data onto one map to be able to show the differences from 2003 and 2009. When looking at the third map you can see exactly how the mean and weighted mean has shifted slightly based on the addresses and number of arrests at these locations.

 

  
 Part B

    The next maps I wanted to created dealt with standard distances. I wanted to find the standard distance of arrests for 03 and 09 to one standard deviation. One standard deviation allows for 68% of the arrests to fall within that area. Along with the standard distances I also wanted to include the weighted mean centers to show where it fell inside the standard distances. The standard distances tool was located in the arctoolbox. My input feature class was the arrests for each year. After computing this tool I was able to see exactly where the concentration of the arrests occurred for the given year. I wasn't surprised when I saw that these arrests fell within a few blocks of Water Street. After completing the standard distances for 03 and 09, I wanted to make a map showing how they compared with each other. In my observation of the maps, it is easy to see that not had changed from 03 to 09. The standard distance shifted slightly but not much.

Part 3 Z-Scores

    The last part of this assignment dealt with calculating Z-scores for the Eau Claire Block Groups. When looking at the block group properties I was concentrated on the Join_Count column. This is the number of arrests in Eau Claire for 2009. Next I needed to find the mean and standard deviation for the block groups. I was able to find this information by looking under quantities in the symbology tab. Under the quantities tab I was able to find the mean and standard deviation. The mean was 5.4 and standard deviation was 7.8. I wanted to find the Z-scores of just three block groups, 57, 46, and 41.

    First I will talk about block group 57. The observation or number of arrests in this block group was 40. To find the Z-score I had to take the observation minus the mean then divide that by the standard deviation.

Z-score= 1-5.4/ 7.8    Z-score= -.5641

Since my observation of arrests was only 1, this would be considered an outlier, and fall in the third standard deviation.

    Block group 46 had an observation of 40, or 40 arrests in that block group that year. This is a very high number as it fell right by Water Street. Again I used the same mean and standard deviation.

Z-score= 40-5.4/7.8     Z-score= 4.435

With the Z-score being so high, it would fall in the first standard deviation covering 68% of all arrests in 2009.

    Block group 41 had an observation of 10, or 10 arrests in that block group in 2009. This is not that high of a number, yet these still are not considered outliers. I used the same mean and standard deviation numbers to compute this Z-score.

Z-score= 10-5.4/7.8     Z-score= .5897

The numbers in this Z-score would have fallen in the second standard deviation. The final map I wanted to create shows you the different block groups and the standard deviations based on the arrests for 2009. It also shows where the bars are located showing you that where the higher concentration of bars are, the higher the standard deviation is. As I would have guessed, the higher standard deviations fell on Water Street or close too.

    After I created all the maps it was easy to see where the majority of the arrests took place, and if the complaining from residents of the community was warranted. Just by looking at the arrests from 03 and 09 you can see that the concentration of arrests was on or near Water Street. I figured this was the case as Water Street has a high concentration of bars and college students that lose there heads after a few drinks. When looking at my third map of comparing the 03 and 09 arrests, it is hard to find a pattern as to where these arrests took place. They are scattered between Water Street and the old downtown bars by the new confluence project. Although not as many drunk college kids go to the downtown bars, there is still plenty of arrests. I believe that it is more then safe to say that alcohol plays a role with a majority of these arrests from both 03 and 09.

     When comparing the standard distances in my fourth and fifth maps, you can see that the bulk of the arrests fall within the first standard deviation circle. These again are between Water Street and the downtown bars. Looking at the sixth map of having both standard distance circles on it, you can see that the standard distances of arrests shifted ever so slightly. This small shift could be from just one house party between the two years.

    My seventh and final map looked at arrests for the block groups based on standard deviations. Comparing my seventh map to maps one and two, this backs up the reasoning why the standard deviations for Water Street and downtown are so high. This is were the majority of the arrests took place.

     After finishing all of my maps and having them laid out I do not see a reason for many of the residents of Eau Claire to complain about the ruckus the college students cause. Yes, fights and disorderly conduct is bad, but when you live in the third ward of Eau Claire which is predominately college age kids you have to know that this would occur. The people who have the right to complain in my opinion are the ones who live outside the third ward and downtown. Now there is not many solutions for these people who live in the areas of high arrests, because you can't really just move that easily. A good solution would be to come to an agreement with the neighboring college aged kids on how late you would like them to party if they don't want the police called. Most of the time if there is a fight the cops would be called no matter what however. Seeing how the trend of arrests didn't vary much from 03 to 09, I can almost bet that these stats will be fairly the same today or five years from now.