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Abstract: Our demographic variable is car thefts (reported) per country. Our ecological variable is CO2 emissions (in megatons) per country. Our intermediate variable is unemployment rate. We studied these three variables because we wanted to know if car thefts cause a majority of CO2 emissions, and whether or not unemployment rates cause the CO2 emissions rise. To collect our research, we went to data soucres on the internet; here are such websites we accumulated the data from: Nationmaster.com and Indexmundi.com. Our hypothesis is that when the car theft variable rises, the CO2 emissions variable rises with it. With our research concerning the car theft variable and the CO2 emissions variable, our hypothesis is supported; using the Excel® program's chart function, it shows that the correlation between car thefts and CO2 emissions is apparent.
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Hypothesis: Cars are in use everyday and every waking moment in our lives; it is no surprise that many are stolen. But due to the amount of CO2 emissions released from cars, it is possible that when these crimes are reported, there is a correlation of carbon-dioxide emissions released frequently due to cars that have been stolen. The correlation between them is a polynomial relationship, rising positively.
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Procedure: We used MicrosoftTM Excel®(GoogleTM Docs to .xl format) as our technological tool to finish this project. Our mathematical tool that we used to finish this project is the Chart function on MicrosoftTM Excel® that graphed out data, and helped us figure out if the variable correlate with each other. Our grestest technological tool was the internet, for it helped us research the information we needed to prove our hypothesis and back-up our variables. We searched for variables after we created our hypothesis. We found our variables when we were throwing out variables in demographic form, as they are easily relatable. Our original idea was if drug offences corresponded with biodiversity, but we decided to skip that idea. We wanted to do something that related to crime, and eventually, we tried out car thefts for our demographic variable. After that, it came naturally; cars create carbon-dioxide emissions, and our variable is car thefts. We found our intermediate variable, unemployment rate, when we tried to sum up a cause for car thefts, and most of us in our group believe being jobless is the cause.
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Background: The demographic variable(car theft) measures the amount of car thefts reported per country. The intermediate variable(unemployment rates) measures the unemployment rate(as dictated by the country) per country. The ecological variable(CO2 emissions) measures the amount of carbon-dioxide per megaton for each country. The car theft variable is mostly used in it's own research; most people use it for why we must stop car theft and what kind of cars are stolen. The CO2 emissions variable is mainly used as evidence for climate change, and temperature increase arguments. The unemployment variable is mainly used for proving a poverty variable, and arguments in economic situations concerning the social status. We chose each of our variables because it is more interesting than something easy, and, we were also a bit curious as to whether or not stolen cars cause much of the carbon-dioxide released.
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Analysis: Between our ecological variable and our demographic variable, there is a polynomial relationship, driving positively(Blue graph). Between our intermediate variable and our demographic variable, there is an exponential correlation, driving negatively and not showing much relation to each other(Red graph). Between our ecological variable and our intermediate variable, there is a logarithmic correlation, driving negatively but also showing no relation to each other(Green graph). Due to the failed relationship between our intermediate variable and the other two variables, a relationship between either is not supported. But, our demographic variable and the ecological variable portray the best relation to each other. Even though the intermediate variable does not depict a relation to any of our variables, our original hypothesis of stolen cars and CO2 emissions still show true between each other.
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Conclusion: Our research supported our hypothesis, as proved by the definite correlation between car thefts and the amount of CO2 emissions released. There were many limitations in our research: the unemployment rate is a varying variable, fluctuating immensely in one year. This is caused by the change in regulations and standards for each country percentage of unemployment rate. Another limitation we noticed when researching our variables is the amount of CO2 emissions released by amount; not to poke at the environmental issue, but, we have yet to see this accumulative amount of carbon-dioxide anywhere. One last thing we noticed when researching is the amount of cars stolen; though there is a rather regular amount of cars left with standing, cars that were stolen have a usual motive behind it that each country has different variables affecting. It's very similar to our unemployment variable, but on a larger and specific scale. Now that we know our hypothesis can be supported by a variable, we believe it's important to look for a variable that could refute it. The hypothesis is that poverty increase causes more car theft, which in turn creates more CO2 emissions, and now that we checked our variables, unemployment does not cause or have an effect on car theft. So, this has disproved our theory, and thus, we need to find a new variable to support the car theft variable.


Graphs
external image UnemploymentVsCars.png
external image CarsVsCO2.png
external image CO2VsUnemployment.png


Works Cited

Index Mundi. Web. 16 Dec. 2009. <http://www.indexmundi.com/g/r.aspx?t=0&v=132&l=en.>

Nation Master. Web. 16 Dec. 2009. <http://www.nationmaster.com/statistics.>