data analysis

Omer Bamfleh

Hien Bui

Crystal Escalera

Hussam Fadaq

Miao Zhang

1. Description of the project (including the goal of the project and what important questions the group wants to address)

The topic that I have chosen for the project is ‘Fatal Motor Vehicle Accidents’ which basically deals with dataset that contains information regarding all the fatal vehicle accidents that have happened in the United States from 2011-2015. This dataset contains data of crashes that involve a motor vehicle that was travelling on a road that is usually open to the public and resulted in the death of the motorist or non-motorist within 30 days of the crash. There are also other factors involved in the information which are not only subjected to the crash details.

Basically, the idea is to summarize data so that effective analysis of these accidents can be carried out regarding what are the factors that cause these accidents and find trends or patterns that can help in identifying areas that need to be worked on that can ultimately result in less fatal vehicle accidents.

The questions could involve what states witness the maximum number of such accidents or which trafficways do these result on the max? What factors contribute to such accidents or the weaknesses in the traffic system that if improved could help in reducing the frequency of these accidents.

2. Description of the key elements (variables or attributes in your dataset) pertinent to the goal and why those elements are crucial to answer your questions

The data dictionary of this dataset has a number of attributes and each one of these holds significance in carrying out effective analysis. If I would have to hand pick some then that would include

State name

Traffic way identifier: name of highway or street

Day of week: which day of the week the crash happened

Crash Hour: the time at which the crash happened

Route Signing: type of route at which accident happened

Manner of collision: angle at which the vehicles collided

light condition:the condition of light a t the time of accident

Atmospheric condition: what was the weather like at the time of accident

Basically all these attributes help identifying patterns like what days or time of the day accidents happen more or even help in identifying factors that could cause such accidents such as atmospheric or light conditions, or the manner of collision could help in identifying that.

3. Description of the analytical approach the group plans to use to answer the questions

We could use descriptive analytics in order to define what happened or how it happened to know about what has been happening and what could potentially have caused it. We could use correlations, sampling.

Then moving into predictive analysis, we could predict what could help in reducing these accidents and taking those measures. This again could be done through data mining approaches.

4. Discuss who could benefit from the analysis and how?

Since this mainly relates to the traffic accidents hence this could prove beneficial for the traffic police and departments that deal with road accidents. They could have a good insight into analyzing these and identifying areas where they could do better. If we look in the long run, then even the infrastructure people that build roads and all could also take this information to locate loopholes in their work and improve.