4B Data Analysis Report, By Hayden Meaney

The data analysis group studied the trend of the number of fatigue-related trucking accidents. We analyzed raw data from a survey taken on trucking accidents between 2001 and 2009. The group found the percent of accidents caused by fatigue for each year and created a linear regression analysis. 2008 is an outlier and therefore it was omitted from the next scatterplot we created, which can be seen below. The new scatterplot has a downward linear trend line which could perhaps be accounted for by the implementation of electronic log books. However, the correlation is not strong and there is still work to be done to reduce fatigue-related trucking accidents. Based on this trend line, we extrapolated the data for predicted crashes for this year. A margin of error was calculated for each year described above and then the average margin of error was calculated. Based on the average margin of error and the linear trend line, we calculated between 28,110 and 40,249 deadly trucking accidents caused by fatigue for this year. This number was calculated based on an estimate population size of 2 million commercial truckers on the road this year.

We also compared the Fitbit Flex 2 and Jawbone UP3. We had each team member wear both devices on opposite wrists for two nights. We then recorded the time slept for the Fitbit, UP3 and the time each person fell asleep and woke up, which was based on alarms and recorded bed-times. We then compared the accuracy of both devices. The results are shown below. The Fitbit is clearly more accurate.

-Hayden Meaney