Extra_Credit :)

My favorite statistics benchmark was when we did a benchmark investigating correlation. For the benchmark we had to investigate a problem. I decided to do my project on the graduation rate in Philadelphia and the possible things that could affect the graduation rate.  Some of the possibilities that i chose was the attendance of the students, the amount of low-income students, the amount of students that are non-English speaking, the number of suspensions, the neighborhood that school is located in, and the demographic make up of the school.  I decided to do this project for our quarter two benchmark because Philadelphia itself seems to be experiencing problems within their school system. The average graduation rate for the School District of Philadelphia is 63%. I investigated all 60 public high schools in Philadelphia.

I learned while doing this benchmark is that the sla core values are heavily correlated to my benchmark. I started with inquiry by coming up with questions such as what affects the graduation rate?. My next step I did required research. So with the variables I came up with I researched for each of the 60 high schools in the Philadelphia area. Presentation was that I analyzed all my data in a word document and used graphs to show how these different variables had a negative or positive affect on the schools graduation rate. Collaboration was used in my benchmark for a few of the graduation rates I had worked with a peer to come up with. We worked together because we were both investigating Philadelphia’s high school graduation rates but we had different variables. So collaboratively we helped each other find the graduation rates. I presented my benchmark by doing a word document with graphs and my calculations of each variable. My calculations included the mean, median, mode, min, max, correlation, spread, and standard devation.  These are all things that we have learned over the year when working with univariate and bivariate data.  The last core value is reflection and at the end of the project I wrote a conclusion about what work still has to be done in the School District of Philadelphia and I even gave possible solutions to the problems.

The correlation between the graduation rate and the amount of suspensions is a strong linear negative correlation. The fewer amounts of suspensions you have the higher the graduation rate will be. For the simple fact when students are suspended they miss school, and when you miss school you miss work. I think this is a reliable source to use when you trying to find out how much a school suspensions may affect their overall graduation rate.