3 - Data Analysis HW (2)

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West Texas A&M University *

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6316

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Economics

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Apr 24, 2024

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docx

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2

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Data & Forecasting Homework (25 points) Due 4/5 at 11:59 PM *You may work in groups of 2. * Part I – Answer the following scenario You are a business analyst consultant for small businesses in the Amarillo/Canyon area. You have a potential client approach you that has a small landscaping company that provides landscaping services for commercial and residential properties in Amarillo. Additionally, this business has a commercial store front with the necessities needed to landscape residential yards. They have reached out to you to ask what your business analysis can do for them. They know they want to expand their customer base, but before they can expand their business, their investors and bank want an analysis completed. Explain to this business the factors that they must consider and what must be considered/asked of a business before you can conduct a forecasting analysis. Be explicit in what data you would need to complete the analysis and what type(s) of analysis that you would find to be the most beneficial in this analysis. Part II – Data Collection and Analysis Instructions: Data Collection: Choose a specific agricultural product or commodity (e.g., wheat, corn, soybeans, etc.). Collect historical data on the price of your chosen agricultural product. You can find this data from reliable sources such as government databases that we have discussed in class, agricultural market reports, or commodity trading websites. Ensure the data covers a significant time period, preferably several years. Data Analysis: Perform data cleaning if necessary (e.g., handling missing values, formatting it in the correct order for your analysis Organize the data into a table or spreadsheet with columns for date and price.
Forecasting Methods – Of the 5 methods, choose 3 to complete Graphical Analysis with Trend Lines: Plot the historical data with a trend line and extrapolate the trend to discuss future trends or expected prices. Adjusting for Inflation: Research and find the inflation rates or a price index for the time period covered by your data. Adjust the historical prices for inflation and use the adjusted data for forecasting. Graphically display the difference between your nominal and real data. Adjusting for Population: If applicable, find data on population growth or consumption trends related to your chosen agricultural product. Adjust the historical prices based on population changes and use the adjusted data for forecasting. Moving Averages: Calculate moving averages for your historical price data. You will need to choose an appropriate interval given your data. Explain why you chose this interval and its usefulness in helping forecast future prices. Monthly Price Indices : Calculate monthly price indices based on your historical data. Use these indices to forecast future prices. Forecasting Results and Analysis: Compare the results obtained from different forecasting methods and critique your methods used. Discuss the strengths and limitations of each method in the context of agricultural business forecasting. Provide insights into potential factors that may influence future prices of your chosen agricultural product.
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