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# Descriptive Paper

846 words - 4 pages

Descriptive Statistics Paper
Research and Evaluation I
RES/341
July 20, 2011
Patricia Towne
University of Phoenix

Descriptive Statistics Paper
Last week, team C paper included a hypothesis that explained why gas prices were on the rise and the factors that play a part it in. This week, after further research and evaluation team C conducted intense research to support and confirm the articles that explained the different situations that involved crude oil and the reason why it plays a factor on the price of gasoline. Team C thoroughly conducted research with the help of the UOP library and many online sources to help aid in their investigation. There are numerous factors that play a ...view middle of the document...

The best way to measure central tendency and dispersion is to research all areas, not just the area that you live and reside but the surrounding areas. You have to take in account that in the rural areas gas prices may be higher because of the distance the truck has to travel to dispense the gas. Without looking at any graphs, reading any research data, and without looking at any previous data, we know this is a major problem with a mean that is higher than normal.
The data set used in the frequency distribution and histogram was the ten most populated states in America. The gas price in each state was used to calculate the frequency and percentage of that states demand for gas. From the data collected and analyzed in the histogram and the frequency chart, it shows that the reason for gas prices being high in America is not to be blamed on supply and demand because there are other factors which have a major effect on the issue. The chart shows that from the ten most populated states in America, which should have the highest demand for gas, but instead some of the states listed on the ten most populated were not close to the top ten in cost per gallon.
The best central tendency for measuring the collected data was the mean. By finding the pull of the mean, we can properly see the direction our chart or graph will lean most; thus the skew of the distribution can be analyzed more clearly. Our data shows that there are no skew at this time but over time the mean will pull to the left, which will result in a skew...

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