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Car Accidents & Cell Phones. By: Hongtao Xu Sasha Hochstadt Logan McLeod Heather Samoville Christian Helland Meng Yu. Objective. Why? Recent Legislation Is it Valid? Justifiable? What? To determine a possible correlation between traffic fatalities and cell-phone users How?

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car accidents cell phones

Car Accidents & Cell Phones

By: Hongtao Xu

Sasha Hochstadt

Logan McLeod

Heather Samoville

Christian Helland

Meng Yu

objective
Objective
  • Why?
  • Recent Legislation
  • Is it Valid? Justifiable?
  • What?
  • To determine a possible correlation between traffic fatalities and cell-phone users
  • How?
  • Collect data of traffic fatalities and cell-phone subscription
  • Setup valid model and find relationship between them
initial hypothesis
Initial Hypothesis
  • Traffic accidents are increasing over time
  • After the introduction of cell phones traffic accidents will increase at a higher rate
gathered data
Gathered Data
  • Estimated # of Cell Phone Subscribers1985-2002
  • Traffic Fatalities1966-2000
  • # of Registered Vehicles1966-2000
  • # of Licensed drivers1966-2000
  • Resident Population 1966-2000
  • Fatality Rate per 100k Registered Vehicles 1966-2000
modified hypothesis
Modified Hypothesis
  • Findings:
    • Fatalities from car accidents are actually decreasing over time
    • Cell phone subscribers are increasing exponentially over time
  • As fatalities continue to decrease over time, the introduction cell phones will cause them to decrease at a slower rate
  • In order to show this we must compare the periods before and after cell phone use
slide8

Fatalities as a Function in % Change of Cell Phone Subscribers

After

Cell

Phone

Use

LN(Fatalities)

Before

Cell

Phone

Use

Error

Year

regression results in time series
Regression Results in time series

LN(FATALITY) = 75.5532 - 0.0364069*YEAR

LN(FATALITY) = 53.4660 - 0.0252678*YEAR

Before Cell Phone

After Cell Phone

quantifying the cell phone effect
Quantifying the Cell Phone Effect
  • Extrapolate pre-cell phone regression into cell phone regression
  • Calculate expected # of fatalities and % difference from actual
  • Find relationship between % error and # of cell phone subscribers
results
Results

FATALITY = -1.309 + 0.08443*LOG(CELLPHONE)

conclusions
Conclusions
  • A strong correlation between cell phone subscriptions & fatality rate exists.
  • Our model exhibits a logarithmic relationship.
  • We estimate that since 1991, cell phones have caused more than 40,000 deaths.
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