The data that we have chosen to analyze contains information about each county in Virginia and consumer health in that county.
The health data is comprised of participant reported information involving various health related issues including obesity, physical inactivity, and the prevalence of sexually transmitted diseases, among others. The purpose of the health data that we are using is to draw conclusions about health related problems in various communities and relate those problems with movement of students from secondary to postsecondary education.
The movement defined above can be quantified using data about graduation rates and graduation rates within four years within secondary education and acceptance to postsecondary schools. The potential impact of our project would include reducing health related issues in communities through awareness and overall community support including directing money and programs toward struggling areas.
''How do different health factors affect graduation rates in different counties in Virginia?''
This question seeks to address how likely students are to graduate from secondary school, as compared to their overall measures of health and wellness, and then further refine these relationships by county. As certain health factors come into play in a student's life, their overall life choices are affected, so we aim to zoom in on the health factor's correlation with graduating from high school.
Virginia could highly benefit knowing if there is a relation between particular health factors and high school graduation. Factors such as substance abuse, obesity rates, low birth weights, amongst others, may have valuable data relations between student success in school up to a college level.
By analyzing these different factors in relation to school success, Virginia can work to better equip struggling districts in areas where they may need help. For example, by analyzing data we may find that obesity rates have a huge impact on success in school. Then in districts where obesity is more prevalent, Virginia could employ classes and programs in the district to better educate parents and their children alike on the issue.
Excluding even the more obvious relations, Virginia could also use this data in order to find patterns between related factors, and take that into account when working to solve issues in the general population. For example, perhaps a large number of districts display a high prevalence of obesity. Data may show that these same districts also have a low number of access to physical fitness opportunities in the area. This could show a possible relation between these two factors, which helps in developing classes and programs to tackle the issue.
This kind of data could go even further than just the state of Virginia, large scale data aggregation could help other states and perhaps even countries as well.