So as I started on this assignment, I had it in my head I was going to do it on xbox one sales. Unfortunately, I did not realize just how impossible it was to find sales data for the xbox one for each state let alone each county for a specific state. All I could ever find was the national sales. So finally that idea was scrapped and my dad gave me the idea to do it on corn production in Colorado by each county, and what do ya know, PERFECT!

Now, as you can see in the first picture, I did find data from 2008 for Colorado counties and corn production. After tidying up the data, (I had to take out the descriptions in each number such as acres, bushels, M for millions, change the millions from decimal to full numbers) I just started with a simple regression analysis between planted acres, harvested acres, and production in bushels. Using production as my dependent and the other two as my independent variables I came up with a decent regression model. The F statistic and R Square values were great, but my t and p values were not so great.

Next onto my second regression, I added yield and dummy variables to my independent variables. Yield was the yield of bushels per acre for each counties harvest. My dummy variables are actually what I based my question on. The dummy variable was if the corn was irrigated or non irrigated. My question was whether or not being irrigated or non irrigated had any effect on how much each crop would produce. After adding the dummy variables to the second and third regressions, ( which are the third and fourth pictures) I concluded that they did not have an effect on how much the crops by county produced. After the addition of them though, it did increase the accuracy of my model, but at the same time it also decreased my F, t, and p values. Finally I just created a regression model using just dummy variables and my dependent production variable. The model turned out terrible with low everything. So in the end my question was answered and being irrigated or not had no effect on the production of a crop depending on the county conditions.

Now I know I didn’t have nearly enough data to try it, but the trend analysis just really stuck in my head after we talked about it Mr. Holman. I attempted to run two trends, but both came out to be quite poor, obviously because of the lack of data. But after talking with my family ( who are all farmers, and make a living from it) I can conclude that if I did have data spanning from 2008 to the present that it would be going in a downward motion as far as production. I learned that since 2008, there has been a decrease every year in the amount of water that was available for use, due to the cold dry winters, and the hot dry summers with no rain. So a decrease in water means a decrease in the amount of acres being planted, thus a decrease in the amount harvested and produced. But at the same time, since there was / is somewhat of a shortage, corn prices have gone up significantly. Basic economics, high demand low quantity results in higher prices.

I just wanted to thank you Mr. Holman, you have been one of my favorite professors at CSU-P and just have a great way of teaching and not letting any of the BS get into the lectures that you give, you were always there if we needed help, and very understanding if we understood something wrong or didn’t understand something at all. If you have any questions or comments, obviously you can leave them on here or you can email me.

Best Regards,

Luke Clementi