(a) Construct a time series plot.160160160140140140120120120100100100-8080806060604040402020200+++0-+++0 1 2 3 4 5 6 7 89 10 11 12 130 1 2 3 4 5 6 7 8 9 10 11 12 130 1 2 3 4 5 6 7 89 10 11 12 13MonthMonthMonth160140120100+806040200+0 12 3 478 9 10 11 12 13MonthWhat type of pattern exists in the data?The data appear to follow a horizontal pattern.The data appear to follow a cyclical pattern.The data appear to follow a seasonal pattern.The data appear to follow a trend pattern.Sales The following time series shows the sales of a particular product over the past 12 months.MonthSales110513531204105906120714581409.10010801110012110(a) Construct a time series plot.160160160140140-140-120-120-120+1001001008080806060604040402020200++0 1 23 4 5 6 7 8 9 10 11 12 130 1 234 5 6 789 10 11 12 130 1 2 3 4 5 6 7 89 10 11 12 13MonthMonthMonth160 TSales

The following time series shows the sales of a particular product over the past 12 months. Month Sales 1 105 2 135 120 4 105 5 90 6. 120 7 145 8 140 9 100 10 80 11 100 12 110 (a) Construct a time series plot. 1601 160 - 160- 140- 120- 100- 140- 140 120 120 100- 100- 80 80 80 60 40 60 60 40 40 20 20 20 0 1 2 3 4 5 6 7 8 9 10 11 12 13 0 1 2 3 4 5 6 7 8 9 10 11 12 13 0 1 2 3 4 5 6 7 89 10 11 12 13 Month Month Month

The following time series shows the sales of a particular product over the past 12 months. Month Sales 1 105 2 135 120 4 105 5 90 6. 120 7 145 8 140 9 100 10 80 11 100 12 110 (a) Construct a time series plot. 1601 160 - 160- 140- 120- 100- 140- 140 120 120 100- 100- 80 80 80 60 40 60 60 40 40 20 20 20 0 1 2 3 4 5 6 7 8 9 10 11 12 13 0 1 2 3 4 5 6 7 8 9 10 11 12 13 0 1 2 3 4 5 6 7 89 10 11 12 13 Month Month Month

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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In agricultural economics, a “supply response function” describes how supply of a commodity responds to changes in the price of that commodity. Year Seeded Area (hectares) Harvested Area (hectares) Average Yield (kg per ha) Production (tonnes) Price per Tonne ($/tonne) 1966 1,317,000 1,317,000 1,630 2,150,000 65 1967 1,424,000 1,424,000 1,720 2,449,000 60 1968 1,376,000 1,376,000 1,800 2,477,000 48 1969 1,012,000 1,012,000 1,720 1,742,000 46 1970 567,000 567,000 1,465 830,000 52 1971 1,019,000 1,019,000 1,975 2,014,000 50 1972 1,052,000 1,052,000 1,785 1,878,000 68 1973 1,214,000 1,214,000 1,725 2,095,000 158 1974 1,133,000 1,133,000 1,415 1,605,000 147 1975 1,255,000 1,255,000 1,690 2,123,000 130 1976 1,538,000 1,538,000 1,820 2,803,000 103 1977 1,295,000 1,295,000 2,125 2,749,000 98 1978 1,376,000 1,376,000 2,055 2,831,000 133 1979 1,214,000 1,214,000 1,680 2,041,000 170 1980 1,336,000 1,336,000 1,425 1,905,000 203 1981 1,577,900 1,577,900…
PART A The following table shows quarterly sales (in thousand units) for a product over 4 years. The overall sales average for the entire 4 years is 156.5625 (thousand units). Fill in the missing values assuming there is no trend. Round seasonal indexes to 4 decimal places. Report Averages accurate to at most 2 decimal places. Report Actual sales ('000) accurate to the nearest integer. Year 1 Year 2 Year 3 Year 4 Average Seasonal Index Quarter 1 86 93 95 0.6004 Quarter 2 205 207 198 1.2838 Quarter 3 154 159 153 175 160.2 1.023 Quarter 4 184 167 158 175 171 1.092 PART B Suppose actual quarterly sales (in thousands) for Year 5 are 82, 196, 178, and 180 respectively. Assuming there is no trend, forecast sales for the four quarters of Year 5. Use seasonal indexes (rounded to 4 decimal places) from Part A. Report forecast answers as integers accurate to the nearest thousand. Quarter 1 forecast = thousand Quarter 2 forecast= thousand Quarter 3 forecast= thousand Quarter 4 forecast= thousand…
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II.
Based on the following graph, what is the year when the largest decrease in GDP took place ? GDP (change YoY) 6% 5% 4% 4% 3% 3% 3% 3% 2% 2% 1% -1% -1% -8% 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010o 2011 2012 2013 2009 2001 2005 2007