Pledged Camden Lemond
My project is describing the relationship between per capita personal income. average miles per driver, and the minimum legal drinking age within certain areas by using a panel of observations from 1982 to 1988. My project will try to answer the question, “Does a lower per capita income increase the number of fatalities from drunk driving?” My main variable of interest is the traffic fatality rate. It can answer my question because it will show the overall fatalities caused by specific variables. I am also looking at the minimum legal drinking age, average miles per driver, per capita personal income, and the mandatory jail sentence variable. I want to see if these variables dissuade individuals from drinking and driving. My numeric variables are the average miles per driver, minimum legal drinking age, per capita personal income, and traffic fatality rate. My categorical variable is the mandatory jail sentence.
I drew this data from the Ecdat package.
-mrall (numeric variable): Units: Deaths per 10000 Traffic fatality rate. This variable will show the fatality rate.
-mlda (numeric variable):
Units: People Minimum legal drinking age. This variable will show the ages of the drivers in this dataset, thus showing the primary age group in fatal traffic accidents.
-vmiles (numeric variable):
Units: Miles Average miles per driver. This variable will show how far our drivers drove before their fatal traffic accident. It’s important because it will show whether distance, is important in fatal traffic accidents.
-perinc (numeric variable):
Units: Dollars Per capita personal income. This variable shows our sample’s income level. It will help in determining whether or not lower or higher income levels are related to fatal traffic accidents.
-jalid (categorical variable):
Units: Yes or No Mandatory jail sentence. This variable determines wether or not there is a mandatory jail sentence as punishment for fatal traffic accidents.
mlda (Minimum Legal Drinking Age) Min : 18.00 Mean: 20.46 Max: 21.00 Standard Deviation: 0.8990255 Variance: 0.8082468
vmiles (Average miles per driver) Min : 4.576 Max: 26.148 Mean: 7.890754 Standard Deviation: 1.475659 Variance: 2.177569
perinc (Per capita personal income) Min: 9514 Max: 22193 Mean: 13880.18 Standard Deviation: 2253.046 Variance: 5076218
mrall (Traffic Fatality Rate) Min: 0.82121 Max: 4.21784 Mean: 2.040444 Standard Deviation: 0.5701938 Variance: 0.3251209
Correlational Matrix mlda vmiles perinc mrall mlda 1.00000000 0.05927872 0.20308721 -0.09089998 vmiles 0.05927872 1.00000000 -0.08019966 0.39682980 perinc 0.20308721 -0.08019966 1.00000000 -0.49881065 mrall -0.09089998 0.39682980 -0.49881065 1.00000000
mlda: plot(Fatality\(mlda) vmiles: plot(Fatality\)vmiles) perinc: boxplot(Fatality\(perinc) mrall: plot(Fatality\)mrall) Outcome & Main Variable of Interest: plot(Fatality\(perinc, Fatality\)mrall)