John Mitchell Mazala Moody Professor Brown Math 36 April 1st, 2020 Final Project Script Crime. We’ve all heard about it on the news or on social media. And what we hear about the most— despite the fact that it is by far not the most common kind of crime—is violent crime, defined by the FBI as consisting of four offenses: murder and non-negligent manslaughter, forcible rape, robbery, and aggravated assault. But exactly how common is violent crime across the country? Do certain areas experience more violent crime? And if so, why? What factors are linked to violent crime, and why? What is the link between violent crime, poverty, and education? Stay tuned to find out! In terms of total violent crimes committed, in 2011 there were an estimated total of 1,203,564 violent crimes committed nationwide, with the vast majority of 62.4% being instances of aggravated assault. (I plan to get clearer images) But where did those crimes take place? Did certain areas experience more violent crime than others? If so, why? First, as we can see, many of the major clusters of violent crime are located in major cities, including New York, Los Angeles, and Chicago. If those three cities sound familiar, they also happen to be the three largest cities in the United States. So violent crime has a definite correlation with large population clusters, but is this simply because there are more people around to commit crimes, or are there other factors at work here? Let’s look closer. If we look at the numbers of families with income below poverty level, what do we see? The clusters match up very closely with those of violent crime, with the largest numbers centered again on major cities such as New York, Los Angeles, and Chicago. So as we can see, there is a very close correlation between there are a lot of people living in poverty, and where a lot of people are committing violent crimes. Note that these are raw numbers, not percentages, but they can still give us a valuable picture of where the most crime is occurring, and why that might be. But let’s look closer still. When we look at which areas have the most people 25 years of age or older who have completed less than high school, the map again shows us massive clusters of people in the big cities again. Los Angeles County features a whopping 23.73% of people 25 years of age or older having completed less than high school. Bronx County, New York, is even worse, with a staggering 30.71% percent. What else do these areas have lots of? You guessed it, violent crime! So it is clear that violent crime is linked very closely with poverty, and perhaps even more closely with a lack of education. So what should be done to fix the problem? Well, to start with, increasing funding and access to education has been shown many times to decrease people’s chances of living in poverty and of committing violent—and other types of—crime. (im trying to find more reliable data that compares education, pov ...

1. John Mitchell
Mazala Moody
Professor Brown
Math 36
April 1st, 2020
Final Project Script
Crime. We’ve all heard about it on the news or on social media.
And what we hear about the most—
despite the fact that it is by far not the most common kind of
crime—is violent crime, defined by the
FBI as consisting of four offenses: murder and non-negligent
manslaughter, forcible rape, robbery, and
aggravated assault. But exactly how common is violent crime
across the country? Do certain areas
experience more violent crime? And if so, why? What factors
are linked to violent crime, and why?
What is the link between violent crime, poverty, and education?
Stay tuned to find out!
In terms of total violent crimes committed, in 2011 there were
an estimated total of 1,203,564 violent
crimes committed nationwide, with the vast majority of 62.4%
being instances of aggravated assault.
(I plan to get clearer images)
But where did those crimes take place? Did certain areas
experience more violent crime than others? If
so, why? First, as we can see, many of the major clusters of

2. violent crime are located in major cities,
including New York, Los Angeles, and Chicago. If those three
cities sound familiar, they also happen
to be the three largest cities in the United States. So violent
crime has a definite correlation with large
population clusters, but is this simply because there are more
people around to commit crimes, or are
there other factors at work here? Let’s look closer.
If we look at the numbers of families with income below
poverty level, what do we see? The clusters
match up very closely with those of violent crime, with the
largest numbers centered again on major
cities such as New York, Los Angeles, and Chicago. So as we
can see, there is a very close correlation
between there are a lot of people living in poverty, and where a
lot of people are committing violent
crimes. Note that these are raw numbers, not percentages, but
they can still give us a valuable picture of
where the most crime is occurring, and why that might be.
But let’s look closer still. When we look at which areas have the
most people 25 years of age or older
who have completed less than high school, the map again shows
us massive clusters of people in the
big cities again. Los Angeles County features a whopping
23.73% of people 25 years of age or older
having completed less than high school. Bronx County, New
York, is even worse, with a staggering
30.71% percent. What else do these areas have lots of? You
guessed it, violent crime!
So it is clear that violent crime is linked very closely with
poverty, and perhaps even more closely with

3. a lack of education. So what should be done to fix the problem?
Well, to start with, increasing funding
and access to education has been shown many times to decrease
people’s chances of living in poverty
and of committing violent—and other types of—crime.
(im trying to find more reliable data that compares education,
poverty, and violent crimes) still need to
add
Sources:
https://ucr.fbi.gov/crime-in-the-u.s/2011/crime-in-the-u.s.-
2011/violent-crime/violent-crime
https://en.wikipedia.org/wiki/List_of_United_States_cities_by_
population
https://www.socialexplorer.com/a9676d974c/explore
https://ucr.fbi.gov/crime-in-the-u.s/2011/crime-in-the-u.s.-
2011/violent-crime/violent-crime
https://en.wikipedia.org/wiki/List_of_United_States_cities_by_
population
https://www.socialexplorer.com/a9676d974c/explore
Project Description
CIS 4321 Spring 2020
Dr. Batarseh
In this project, you experience the full cycle of the data mining
process. Below, I explain the different stages of the
project.Project Objectives
At the conclusion of this project assignment, participants should
be able to:

4. · Write a project proposal
· Identify a dataset to mine
· Mine a dataset and write-up the insights gathered from the
results
Requirements
For the final project in CIS4321 , you are going to mine a
dataset and define a project scope, implementation and analysis.
The dataset should be interesting, non-trivial and should have at
least 6 attributes and on the order of 1000s (or more) instances.
Some examples include data related to business, consumer
behaviors, social-network information, etc. You could select a
business problem that can be addressed through data mining.
The following links are some sites to public datasets.
· www.data.gov
· www.kaggle.com/datasets
· www.archive.ics.uci.edu/ml/datasets.html
· www.aws.amazon.com/datasets
· www.data.worldbank.org
· www.pewinternet.org/datasets
· www.labrosa.ee.columbia.edu/millionsong
· www.sports-reference.com
· www.wunderground.com/history
· www.yelp.com/academic_dataset
· www.developer.bestbuy.com/apis
Project Proposal (Due April 20th)
Formally write up your proposed project. Your write-up should
address each below point individually, It should be single
spaced, grammatically correct, and submitted to Blackboard by
the deadline. Include in your project the following:
1. Project name (descriptive and concise).
2. Significance of the project
3. Dataset description
a. Describe the contents of the dataset.
b. Link to where it can be located
c. Dataset format
d. Provide a description of the attributes and target variable.

5. 4. Implementation
a. What type of pre-processing, EDA and modeling you
anticipate using?
5. Results
a. Why are the results useful?
b. Who would be interested in the results?
Dataset Mining
Your project should deliver on the functionality described in
your project proposal. As part of this, you will need to perform
data preprocessing (as needed), exploratory analysis of the
dataset (including visualizations), modeling and testing and
evaluation. You should also consider feature selection to help
improve the predictive power (accuracy) of you approach.
Technical Report (Integrated in Jupyter Notebook).
You need to write a technical report describing your approach
and findings. Your report must be written in Jupyter Notebook
and interleaved with your python code. The report should be
organized, clear, concise and easy to understand and follow.
Your notebook should have the following sections at a minimum
(in the order given below):
1. Introduction: This section must briefly describe the dataset
you used and the data mining task you implemented. Briefly
describe your findings.
2. Data Analysis: This section must provide details about the
dataset. You must include:
a. Information about the dataset itself, e.g., the attributes and
attribute types, the number of instances, and the attribute being
used as the label.
b. Relevant summary statistics about the dataset.
c. Data visualizations highlighting important/interesting aspects
of your dataset. Visualizations may include frequency
distributions, comparisons of attributes (scatterplot, multiple
frequency diagrams), box and whisker plots, etc. The goal is not
to include all possible diagrams, but instead to select and
highlight diagrams that provide insight about the dataset itself.
d. Note that this section must describe the above (in paragraph

6. form) and not just provide diagrams and statistics. Also, each
figure included must have a figure caption (Figure number and
textual description) that is referenced from the text (e.g.,
“Figure 2 shows a frequency diagram for ...”). You should
provide you source code using Jupyter Notebook and files.
3. Modeling Results: This section should describe the modeling
approach you developed and its performance. Explain what
techniques you used, briefly how you designed and implemented
model, how you tested the predictive ability, and how well it
performs.
4. Conclusion: Provide a conclusion of your project, including a
short summary of the dataset you used and any of its inherent
challenges, the modeling approach you developed and any ideas
you have on ways to improve its performance
Project Submission
Submit your project to blackboard by the due date, no late
submissions will be accepted.
You should submit a well-documented Jupyter Notebook and
dataset files. Submit both .ipynb and .pdf files, name your files
First_Lastname_FinalProject.ipynb.
Grading Guidelines
This assignment is worth 100 points + 10 points bonus. Your
assignment will be evaluated based on a successful compilation
and adherence to the program requirements. We will grade
according to the following criteria:
· 15 pts for project proposal
· 50 pts for implementation
· 25 pts for relevance/originality of project
· 25 pts for technical rigor and complexity
· 35 pts for technical reporting in a Jupyter Notebook
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