As a Statistician for Decision Innovation Solutions, Jing Tang is responsible for analyzing agricultural data to help clients to make better strategic business decisions, and to assist co-workers improve model prediction and model estimation preference.Jing works with clients and coworkers on data cleaning, modeling estimation, optimization, prediction, machine learning, and risk analysis, as well as providing reliable analysis results. So far, she has been involved in several projects, such as using the prices of soybean oil, corn, and heating oil to predict yellow grease price, optimizing different factors’ conditions to increase yields coming from byproducts.Jing comes from Beijing, the capital of China. She earned a Bachelor degree in Food Science and Technology at the Beijing Business and Technology University (BTBU), and obtained a M.S. degree in Food Science at the University of Missouri (MU), Columbia. Currently, Jing is enrolled as a Statistics student at MU. Jing has the ability to combine both science and statistics knowledge together and to assist clients and colleagues in analyzing data, especially in the agricultural industry.
In Iowa, the harvesting season for both corn and soybean is underway. “U.S. farmers are expecting higher production of soybeans, while expecting a slightly decreasing corn production”, saying by the Newsletter from USDA published on Aug 10th, 2018.
Nowadays, more and more people pay attention to data and information and how to use them in a proper way. Analyzing data includes not only collecting raw data but also how to convert the numbers to inform a company's strategy and decision making. A small improvement in data analysis can lead to a big financial return for companies.
For the first dataset, gasoline's price is higher than ethanol price, the correlation between daily ethanol price and gasoline price
The Chinese government indicated that the expected fuel ethanol production will be 4 million Metric tons (1.339 billion gallons) per year during the 13th Five-Year Plan. In 2017, ethanol production stands for 2.6 million tons (0.871 billion gallons) per year, increased 0.5 million tons (0.167 billion gallons) per year, from 2.1 million tons (0.703 billion gallons) in 2016.
We have done an analysis to understand the relationship among monthly average ethanol prices versus ethanol ending stocks, corn prices, and gasoline prices. The major finding was that all of three predictors, i.e., ethanol ending stocks, corn prices, and gasoline prices, have statistically significant influences on monthly average ethanol prices.
The Chinese government recently indicated that the expected ethanol production will be 4 million tons (1.2314 billion gallons) per year for the next five years. Current ethanol production in China stands at 2.1 million tons (0.646 billion gallons) per year.
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