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Unformatted text preview: Recitation for week #13 (starting Sunday, Apr 25, 2010) and Assignment #12: Forecasting OR&IE 3120, Spring 2010 This assignment contains a computer lab and homework problems. All problems should be handed in as Assignment #12 which is due at noon on Wed, May 5, 2010. The data for this lab come from a production line of Stove Top products. The data set is in the file StoveTop.csv . There are three variables, year , month , and Sales 93 . In this lab, you will forecast Sales 93 , sales for line 93. First read the data and plot the sales as a time series: dat = read.csv(’StoveTop.csv’,header=TRUE) attach(dat) Sales_93_ts = ts(Sales_93,start=c(2000,4),frequency=12) class(Sales_93_ts) plot(Sales_93_ts,type="b") Notice the way the Sales_93_ts was converted to class ts (time series). R objects of class ts contain, besides the data, information such as frequency and starting date. Here the frequency is 12 (monthly) and the starting date is April 2000. The frequency and starting date are used in plotting and, more importantly, seasonal forecasting (see below). Also plot the sales by month with colors numbered 1, 2, 3, and 4 for years 2000 to 2003. (In R , each color has a number.) plot(Sales_93~month,col=(year-1999)) Problem 1 Are there any months that are outlying in that the total sales for that month are low compared to sales for the same month in other years. Which month and year are they? Conjecture why they might be outlying. You should consider plotting the data inthey?...
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This note was uploaded on 03/18/2012 for the course ORIE 3120 taught by Professor Jackson during the Spring '09 term at Cornell.
- Spring '09