STATISTICS IN A BUSINESS ENVIRONMENT

Statistics in a business environment



Statistics in a business environment

The project involves looking at the gas prices trend that have been there for the past 28 years, and to forecast the gas prices in the future so as to predict the future of the delivery business. Gas prices are crucial for any business, however, when it comes to the delivery business nothing is more interconnected with it than gas prices, as the gas prices increase so does the cost of doing business increases for the delivery industry. As a business entity, the sole motive of doing business is to maximize the revenue generation by minimizing the costs associated with conducting the business. However, due to extreme dependence on gasoline in recent time, the gas prices have taken an exponential hike, which will be observed in the coming years as well. As a result, the company wants to analyze its cost in order to predict the revenue generation in the future, and be able to forecast the future of the company, and what impact will these rising gas prices have on the company.

To perform such an analysis of the gasoline prices, the data has been collected from the Consumer Price Index, which lists the monthly average gas price per gallon in US cities from the year 1982 to 2010. The data was analyzed by performing a linear regression analysis. First of all, the monthly averages of gas prices within each year were transformed into an annual average of gas prices. Then these annual averages of gas prices are taken to be the dependent variable in relation to the years that are considered to be the independent variable for the analysis. Both the independent and dependent variable were then put into a scatter plot and a line of best fit was drawn within the data set by regression analysis. According to the regression analysis, the slope of the line of best fit for the data set came out to be 0.06, which indicates that each year the price of the gasoline per gallon increases by 6 cents. Whereas, the y-intercept for the data set comes out to be 0.62, meaning that the gas prices per gallon in the year before 1982 should be 62 cents. However, if one observes the gas prices of today, one would simply reject the regression analysis, since the analysis seems very far away from the reality. According to the analysis, the gas price for the year 2010 should be around $2.40 per gallon; however, the actual price of gasoline per gallon in the year 2010 was $2.80. This is largely due to the fact that gas prices are highly inelastic and highly depends upon the international market. Moreover, the consumption of gasoline in recent years has sky rocketed, which in turn has led to the exponential increase in the gasoline prices. Furthermore, when I tried to extrapolate the data set to the year 2020, I found out that the gas price per gallon ...