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1. Collect price data for any product, input, or resource. You will need data for 20 years. The years do not have to be sequential.

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1. Collect price data for any product, input, or resource. You will need data for 20 years. The years do not have to be sequential. There can be gaps, even large gaps in your data. You just need 20 years. If you stumble across a data set with more than 20 years, use them all. If you have a good data set, but are a little short of 20 years, call me to discuss. It is important that the product, input, or resource has remained relatively the same over the years you have collected. For example, milk, bacon, and eggs; oil, coal, and natural gas; plywood, cement, and shingles; etc. are roughly the same today as they were 20 years ago. While computers, cars, and televisions are vastly different. Do not pick something that has changed drastically over the last 20 years. 2. Lay your data out in Excel. At first there should be three columns. These are: Year, Price of the Item you picked, and the CPI for that year. There should be at least 20 rows, one row for every year. 3. Next, use Excel's formulas to create a new row using your nominal data and the CPI to adjust the raw (nominal) price to a new inflation adjusted price. Do this for every year. If you have done it correctly, the farther back in history you go, the farther apart will be the nominal and inflation adjusted price. 4. Next, create a graph of your raw data and your inflation adjusted prices. Years should be on the X axis while the nominal and adjusted prices should be on the Y axis. The XY Scatter plot graph is the easiest way to make this work. A line graph is not appropriate. (Do you know why?) 5. Finally, interpret your results. Has the product you picked moved roughly with inflation? Has it risen faster than inflation? Or has it risen slower that inflation? How do you know

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