anandb7248 / F.B.I.-Crime-Analytics-and-Visualizations

Cal Poly, Stat 331 Final Project. Using R Studio and the Shiny Library to create interactive web app

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Stat331-Final_Project

Stat 331 Final Project - [F.B.I. Crime Analytics and Visualizations] Taken Spring 2017 at California Polytechnic San Luis Obispo. The project calls for a creation of an interactive web app using R Studio and the Shiny Library.

By Matt Jimenez,Anand Batjargal, Andrew Harris, and Owais Sarfaraz

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Description of Data

Our data is from the Federal Bureau of Ivestigation. The Data describes violent crime in the United States from 1996 to 2015. The FBI has partitioned violent crime into four sets with decreasing seriousness: Murder, Rape, Robbery, and Aggravated Assult. If a crime has multiple offenses occuring, only the most serious offense is counted. The data is composed into 24 different tables, where each table represents different granularity of focus.

  • Granularity of Focus:

    • United Stats as a whole
    • Region
    • State, Tribal, or other Agency
    • County
    • City
    • State Universities and Colleges
    • Cities and Counties grouped by size
    • Metropolitan Statistical Areas (MSA's)
  • Titles of Data Tables:

    • Table 01: Crime in the United States, by Volume and Rate per 100,000 Inhabitants, 1996-2015
    • Table 1A: "Crime in the United States, Perncent Change in Volume per 100,000 Inhabitants for 2, 5, 10 Years"
    • Table 02: "Crime in the United States, by Community Type, 2015"
    • Table 03: "Crime in the United States, Offense and Population Percent Distribution by Region, 2015"
    • Table 04: "Crime in the United States, by Region, Geographic Division, and State, 2013 -2015"
    • Table 05: "Crime in the United States, by State 2015"
    • Table 06: "Crime in the United States by Metropolitan Statistical Area (MSA)"
    • Table 07: "Offense Analysis, United States, 2011 - 2015"
    • Table 08: List of States to Choose
    • Table 09: "Offenses Known to Law Enforcement, by State by University and College, 2015"
    • Table 10: "Offenses known to Law Enforcement, by state by Metropolitan and Nonmetropolitan Counties, 2015"
    • Table 11: "Offenses Known to Law Enforcement,by State, by Tribal, and Other Agencies"
    • Table 12: "Crime Trends by Population Group (2014-2015)"
    • Table 13: "Crime Trends: By Suburban and Non-Suburban Cities by Population Group (2014-2015)"
    • Table 14: "Crime Trends: by Metropolitan and Nonmetropolitan Couties by Population Group (2014-2015)"
    • Table 15: "Crime Trends: Additional Information Aboust Selected Offenses by Population Group (2014 - 2015)"
    • Table 16: "Rate: Number of Crimes per 100,000 Inhabitants by Population Group, 2015"
    • Table 17: "Rate: Number of Crimes per 100,000 Inhabitants by Suburban and Nonsuburban Cites by Popualtion Group, 2015"
    • Table 18: "Rate: Number of Crimes per 100,000 Inhabitants by Metro and Nonmetro Counties by Population Group, 2015"
    • Table 19: "Rate: Number of Crimes per 100,000 Inhabitants"
    • Table 20: "Murder by State, Types of Weapons, 2015"
    • Table 21: "Robbery by State, Types of Weapons, 2015"
    • Table 22: "Aggravated Assult by State , types of Weapsons, 2015"
    • Table 23: "Offense Analysis: Number and Perent change, 2014-2015" [14,420 agencies; 2015 estimated population 283,415,007]
    • Table 24: "Property Stolen and Recovered, by Type and Value 2015"

References

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Cal Poly, Stat 331 Final Project. Using R Studio and the Shiny Library to create interactive web app


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