Motivate...
Rice is an important crop in Thailand and represents a significant portion of the Thai economy and the labor force. As the video discussed, the rice grows in a flooded area, and farmers either rely on irrigation from rivers or rainfall. This rainfall, in Thailand and many other countries, comes from the monsoon. Monsoons are seasonal reversals, in this case from dry to wet. Since farmers in Thailand rely on the wet monsoon season to grow crops, variations in the monsoon season have severe implications for the economy. Being able to predict the wet season of the monsoon is imperative. Because of the general periodicity of the monsoon, we can utilize a time series to predict the coming and going of the wet season.
Newsstand
- (2011, October, 11). Thailand races to defend Bangkok from floods. Retrieved November 16, 2017.
- Bundhun, Rachel. (2016, June 16). Indian economy’s fate depends on the monsoon. Retrieved November 16, 2017.
- (2010, March 4). Drought Threatens Mekong Crops. Retrieved November 16, 2017.
- Rochan, By M. (2014, July 21). Thailand to Reclaim Top Rice Exporter Status After Weak Indian Monsoon Rains. Retrieved November 16, 2017.
- (2013, May 2017). Bangladesh Crop Insurance: Helping Farmers Weather the Storm. Retrieved November 16, 2017.
Lesson Objectives
- Define, compute, and interpret autocorrelation in a dataset.
- Create an autoregressive model for a dataset.
- Create a moving average model for a dataset.
- Create an ARMA or ARIMA model for a dataset.
- Explain the differences between models, the strengths and weakness of each, as well as when to use each one.