Paper Construction The text of your paper should be organized into the following sections: 1. 4. Overview of your time series. In this section describe the variable that you are trying to forecast. Provide numerical and grapphical . Decomposition. Discuss Whether or not you are going to used the original time series or a transformed time series. Use classical decomposition and STL. Discuss which method you think does a better job at separating the time series into its constituent parts. . Forecast. Choose one of the simple forecasting methods from section 5.2 of your text to provide a forecast of the time series. Analyze the residuals of your time series to assess t. Leave out the last 5 values of your time series for testing. Trainng your model using the other values. Determine the accuracy of your forecast. Use crossvalidation to assess your time series model. Discussion/ Conclusions. You should use times new roman, 12 pt font, single spaced. Each section (or subsection) should receive a heading. Details and Assessment 1. 2. 4. Introduction: In the introduction section of your paper, discuss the time series you were given. When was the data collected, what is the variable of interest you are trying to forecast. Assessment: . Does the introduction have a logical organization? . Has enough background information been provided in order to understand the time series that is being analyzed? :- Has a reasonable explanation been given as to why it might be useful to analyze this time series? . Have reasonable summaries (graphical and numerical) to adequately understand the time series? Decomposition: Describe via decomposition the main features of the time series. a Is there a sufcient description of the time series, as to whether it has a trend, seasonality, etc.? . Was there a suicient description camparing and contrasting classical and STL decomposition? Assessment: - Was the time series properly decomposed and adequately explained? . Forecast: Describe which method you are going to use to forecast your time series. Fit the time series model and analyze the t. Determine the accuracy of your model. Assessment: Was the forecasting method properly described and implemented. Were all of the assumptions properly checked by analyzing the residuals? Were the forecast errors analyzed correctly. Was cross-validation performed and analyzed correctly? Discussion / Conclusions: Discuss what you learned by analyzing your time series. What conclusions can you make? Assessment: - Was there a good explanation regarding what was learned by analyzing this time series? - Was everything wrapped up and succinctly summarized