Topic: What is your Prediction? A time series model is a forecasting technique that attempts to predict the future values of a variable by using only historical data on that one variable. Here are some examples of variables you can use to forecast. You may use a different source other than the ones listed (be sure to reference the website). There are many other variables you can use, as long as you have values that are recorded at successive intervals of time. Currency price: XE (http://www.xe.com/currencyconverter/) GNP: Trading Economics (http://www.tradingeconomics.com/united-states/gross-national-product) Average home sales: National Association of Realtors (http://www.realtor.org/topics/existing-home-sales) College tuition: National Center for Education Statistics (https://nces.ed.gov/fastfacts/display.asp?id=76) Weather temperature or precipitation: (http://www.weather.gov/help-past-weather) Stock price: Yahoo Finance (https://finance.yahoo.com) Main Post: Once you have historical data, address the following: 1.   State the variable you are forecasting. 2.   Collect data for any time horizon (daily, monthly, yearly). Select at least 8 data values. 3.   Use the Time Series Forecasting Templates to forecast using moving average, weighted moving average, and exponential smoothing (see video in Unit 9 LiveBinder). 4.   Copy/paste the results of each method into your post. Be sure to state the number of periods used in the moving average method, the weights used in the weighted moving average, and the value of ? used in exponential smoothing. 5.   Clearly state the “next period” prediction for each method.

The Millau Viaduct, at 1125 ft, is the highest bridge in the world and overlooks the river Tarn in France. An object is dropped from the top of the bridge. Neglecting air resistance, the height of the object at time t seconds is given by the polynomial function P(t) = -16t2+ 1125. Find the height of the object when t = 6 seconds.A. 933 ft.B. 1177 ft.C. 549 ft.D. 1317 ft.