I have always been interested in adult crime shows, but I have never thought to analyze the data and trends of those imprisoned. I decided to analyze juvenile incarceration but apply the same sort of data requirements that one would for adult data. For example, instead of just analyzing the data based on age I also used race and offense. When discussing adult incarceration the topic of race is always brought, so I thought for this data I wanted to include age and race. Because I am looking at the trends of juveniles including the age was important, by putting these sets of data together I would be able to analyze the trends in juveniles from 1997 to 2015. Child Trends provided me with all of the data so I could properly graph and analyze it.

I wanted to set up the analysis by comparing age and offense, this is because I am analyzing juveniles so establishing the age is important. Also seeing the age and offenses together helps make the connection when looking at the correlation between race and offense.

The percentage of juveniles in placement based on year and race was important to me because I wanted to see how the numbers and data progressed over the years for each race. What I found interesting was that Asians and American Indians were quite similar. The only set of data that was unique was Hispanic; which was in the middle of white and black, Asians and American Indians.

Percentage of those in placement based on year and race, between 1997–2015.
Percentage of those in placement based on year and juvenile offense, between 1997–2015.
The correlation between race and juvenile offense.

I went on to analyze the data of those in placement based on year based on juvenile offense. This was particularly interesting because although the percentages seem to be quite low, I included the totals of person and property offenses. The difference between the two is that the property offenses went down between 1997 and 2015 and the person offenses went up in the same time period. In order to properly compare these data sets together I did a graph showing the correlation between them. This graph was very beneficial because it shows which race is correlated with which offense. For example, in the first graph it shows that American Indians have one of the lowest incarceration rates, but in this graph it shows that they were tied for the highest correlation in property offenses.

This data shows the overall trends in juvenile incarceration between 1997 to 2015. What I noticed from the graphs is that it is hard to put a label on trends over the course of 18 years. There are so many different variables to consider when discussing incarceration and I only showed three of them. Although the data may show a higher percentage of one race in placement I don't think that is an accurate representation for an entire race, especially when the data is from one country.