A visualization dashboard that better helps understand the Abortion Statistics collected over the years
The topic for the Project is based on the Abortion Statistics performed by the Center for Disease Control and Prevention (CDC) and the Guttmacher Institute. The CDC first began abortion surveillance in 1969 to document the number and characteristics of women obtaining legally induced abortions.
To dive deeper into this project, we first need to trace the steps back to its origins and understand when abortion was first legalized. Abortion got legalized for the first time in the year 1969 – 1970, in only five states, those five states being Alaska, California, Hawaii, New York, and Washington. It was only four years after the first legalization, that the Supreme Court Roe v. Wade decided to make abortion legal all across the nation. The data gathered is the Abortion Surveillance Statistics datasets which are open source on the CDC website and the Guttmacher Institute.
These articles' data allowed program designers and politicians to pinpoint the demographics of women who abort the most frequently. Induced abortion is primarily caused by unintended pregnancy. It is possible to decrease unwanted pregnancies and further lower the number of abortions carried out in the US by expanding access to and use of effective contraception.
There are several techniques that currently exist and are implemented in previous research papers that deal with exploring and visualizing Abortion Statistics.
The data and the papers by CDC and the Guttmacher Institute visualize the data in their papers using different visualizing techniques. Each is unique in its representation. For example, the CDC uses a really generic visualization technique known as Line Graph representation. A line chart is a graphical representation of information that changes continuously over time. The image that opens this post shows "markers" for data points connected by straight lines that delimit the start, duration, and end of a variable on a timeline.
They plot the Number of Abortions performed per year on the graph and that is the only visualization implemented in their reports and research papers. It is also another form of representation implemented by the Guttmacher Institute. This method of visualization is very common between different organizations and their representation of the statistics for abortion.
There are several information visualization techniques that have been used and implemented in order to accurately and efficiently create visualizations for this project. The key factor of this project is to have effective visualizations that represent the years of data leading up to today.
Thus, in order to create a visualization that can be integrated into a dashboard that would allow the user to swap between them all and learn and understand the data, the following Visualization Techniques were implemented.
A bar chart is the depiction of information, numbers, or data using strips or bars in a graphical form. It is deployed in order to help compare and contrast different data types, their frequencies, and categories of data. A bar chart helps depict the abortion stats from the year 1973 to now for all states in the United States.
A graphical representation of data and information that can morph continuously is known as a line chart. The continuous changes are tracked efficiently with the use of markers on the data points. A line chart is the most commonly used representation of abortion statistics and is simple to understand for any user.
A box plot is a quartile-based distribution of any variable that is present in the statistical illustration. The box’s ends represent the upper and lower ends of the distribution and thus provide the user with an understanding of the minimum and maximum of the data.
These charts are extremely similar to box charts, where the plots display the probability density for the various attributes of the data. It is marked by the median, the IQ range, and sample points. This would help the user understand the median for any or all regions that the user wants to specifically focus on and understand.
Funnel chart helps in displaying the data in different stages of its progress or process. This view of the data can help people understand the data at its basic level and at its maximum growth as well.
A pie chart is a graphical representation that is circular in form, and has sections that represent each portion of the data. In this project, it represents the abortion ratio across the 50 states of the united states.