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Three years of monthly lawn-maintenance expenses ($) for a six-unit apartment house insouthern Florida follow.
Month Year 1 Year 2 Year 3
January 170 180 195
February 180 205 210
March 205 215 230
April 230 245 280
May 240 265 290
June 315 330 390
July 360 400 420
August 290 335 330
September 240 260 290
October 240 270 295
November 230 255 280
December 195 220 250
a. Construct a time series plot. What type of pattern exists in the data?
b. Develop an estimated regression equation that can be used to account for any seasonaland linear trend effects in the data. Use the following dummy variables to account forthe seasonal effects in the data: Jan 1 if January, 0 otherwise; Feb 1 if February,0 otherwise; Mar 1 if March, 0 otherwise; . . . Nov 1 if November, 0 otherwise.Note that using this coding method, when all the 11 dummy variables are 0, the observationcorresponds to an expense in December.
c. Compute the monthly forecasts for next year based upon both trend and seasonaleffects.
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