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Gas Price Analysis Analysis Design and Assumptions In the evaluation of possible independent variables that may impact the dependant variable of vehicle sales, Nissan
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Submitted by cgk01 on April 27, 2008
Category: Philosophy
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Analysis Design and Assumptions
In the evaluation of possible independent variables that may impact the dependant variable of vehicle sales, Nissan Vehicle Sales data for a representative Car (Sentra) and SUV (Xterra) was gathered for the cities of Nashville and New York by month for a 4 year period from 2003 from official Nissan Web-site and other sources.
Our Specific areas that were of interest were gas prices, population density, and average income. Gas Prices data was gathered using the “Petroleum Navigator” tool in the US Department of Energy (DOE) website and “gasbuddy.com”, which contains comprehensive listings of gas prices by different cities for different periods. Income and Population Data were from the 2000 US Census data results and specific Metropolitan City Web-sites.
Gas prices would be represented in the study by the prices of gas in the two cities specified over a four year period. The analysis would presume that as gas prices grow consumers would then purchase more fuel efficient cars of use some other form of transit i.e. public transportation. Thus, it would be presumed that there would be a negative relationship between vehicle sales and gas prices.
Population density would be measured as the population of Nashville and New York. As a result of the census being done every five years the population used was constant over our four year analysis of the data. In more heavily populated areas it is presumed that as the population increases the demand for fuel in that particular area would increase. Thus, it is also presumed that the greater the population density the higher the gas prices would be in a city.
As median incomes become higher, it is presumed that populations would not change their buying preference based on the price of gas. As such, there is expected to be a positive correlation between per capita income and vehicle sales.
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