Once you have historical data, address the following: 1. Apply quantitative forecasting methods in time-series modeling. a. State the variable you are forecasting. b. Collect data for any time horizon (daily, monthly, yearly). Select at least 8 data values. c. Compute moving average and weighted moving average in a time-series model. i. Use the Excel Workbooks for this module to forecast the next period’s value using moving average, and weighted moving average ii. Copy/paste the results of each method into your word document. iii. Be sure to state the number of periods used in the moving average method and the weights used in the weighted moving average. Clearly state the “next period” prediction for each method. iv. Determine which of the two forecasts should be chosen and give the rationale for the decision. d. Identify variables for a regression model. i. Determine which variable from the time series forecast would be an appropriate dependent variable (X) and tell why. ii. Determine which variable from the time series forecast would be an appropriate independent variable (Y) and tell why. e. Develop a simple linear regression model. i. Use the regression function found in Data Analysis located in Microsoft Excel to determine the linear regression model. ii. Based upon the values given, what is the valid dependent variable range?