analytics: a model for prediction

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ANALYTICS: A MODEL FOR PREDICTION Presenters: Whitney Cunningham Jo Pang Robert Talbott Alex Dunagan St. Louis City Homicides

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Presenters: Whitney Cunningham Jo Pang Robert Talbott Alex Dunagan. Analytics: a Model for prediction. St. Louis City Homicides. Overview. Qualitative Analysis Initial Quantitative Analysis Our Model Results Challenges Conclusion. Qualitative Data. Quantitative Data. - PowerPoint PPT Presentation

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Page 1: Analytics:  a Model for prediction

ANALYTICS: A MODEL FOR

PREDICTIONPresenters:

Whitney CunninghamJo Pang

Robert TalbottAlex Dunagan

St. Louis City Homicides

Page 2: Analytics:  a Model for prediction

OVERVIEW Qualitative Analysis Initial Quantitative Analysis Our Model Results Challenges Conclusion

Page 4: Analytics:  a Model for prediction

QUANTITATIVE DATA Explored topics presented in our

qualitative analysis Uniform Crime Report: 1979-2007

AgeRaceWeapon UsedYearMonthsRelation between Offender and Victim

Page 5: Analytics:  a Model for prediction

UCR: HOMICIDES BY AGE IN ST. LOUIS

Page 6: Analytics:  a Model for prediction

UCR: HOMICIDES BY RACE IN ST. LOUIS

Page 7: Analytics:  a Model for prediction

UCR: HOMICIDES BY WEAPON IN ST. LOUIS

Page 8: Analytics:  a Model for prediction

UCR: HOMICIDES BY TIME IN ST. LOUIS

Page 9: Analytics:  a Model for prediction

UCR: HOMICIDES BY RELATIONSHIP IN ST. LOUIS

Page 10: Analytics:  a Model for prediction

CHALLENGES Not divided by neighborhood

Neighborhoods do not all report this data

Missing data in database

No data from 2007-2010

Page 11: Analytics:  a Model for prediction

THE MODEL

Our model will be linked here.

Page 12: Analytics:  a Model for prediction

THE MODELDate Estimated Total

HomicidesActual Total Homicides

Correlation between Estimated and Actual

March, 2010 36 28 0.865

April, 2010 49 42 0.881

May, 2010 68 52 .882

Page 13: Analytics:  a Model for prediction

MARCH 2011

#1: Wells/Goodfellow

#2: Dutchtown

#2: Kingsway West

4

2

2

2

#2: Mark Twain

#2: Mark Twain/I-70 Industrial

2

Page 14: Analytics:  a Model for prediction

THE RESULTS

Page 15: Analytics:  a Model for prediction

4

2#3: Dutchtown

#1: Wells/Goodfellow

3#2: O’Fallon

#3: Kingsway West

2

#3: Mark Twain

2

APRIL 2011

Page 16: Analytics:  a Model for prediction

THE RESULTS

Page 17: Analytics:  a Model for prediction

3 #2: Jeff Vandelou 3

#2: Fairground

MAY 2011

#1: Wells/Goodfellow 4

4

#1: O’Fallon

3#2: Dutchtown

Page 18: Analytics:  a Model for prediction

THE RESULTS

Page 19: Analytics:  a Model for prediction

CHALLENGES TO OUR MODEL

• Demographics

• Categorization

• Time Resources

• Material Validity

• Data Time Frames

Page 20: Analytics:  a Model for prediction

CONCLUSION: OUR PROCESS

Qualitative analysis to

better understand the

situation

Demographic analysis to find

significant trends

Historical analysis for

more accurate prediction

Page 21: Analytics:  a Model for prediction

CONCLUSION: OUR RECOMMENDATION

Long-term NeedsContinuously analyze demographics and their impact on crime, based on each

neighborhood

Intermediate Focus

Ensure that data taken by FBI on homicides are complete and neighborhoods are listed.

Devote preventative resources to crime-susceptible areas

Immediate Resources

Push most resources on neighborhoods with most past homicides, by month

Page 22: Analytics:  a Model for prediction

QUESTIONS?

Please feel free to comment or on question anything.