What type of pattern exists in the data?The time series plot shows a trend pattern with no seasonal pattern present.The time series plot shows a trend pattern, but there is also a seasonal pattern in the data.The time series plot shows a horizontal pattern with no seasonal pattern present.The time series plot shows a horizontal pattern, but there is also a seasonal pattern in the data.(b) Use the following dummy variables to develop an estimated regression equation to account for seasonal effects in the data:X11 if quarter 1, 0 otherwise; x21 if quarter 2, 0 otherwise; x31 if quarter 3, 0 otherwise.%3D(c) Compute the quarterly forecasts for next year.quarter 1 forecastquarter 2 forecastquarter 3 forecastquarter 4 forecastSubmit Answer Consider the following time series.QuarterYear 1Year 2Year 31706761250425235860534778071(a) Construct a time series plot.9090908080807070706060604040403030302020201010101 234 1 2 3 4 1 241 2 3 4 1 2 3 41241 2 3 41 23 41234Year 1Year 2Year 3Year 1Year 2Year 3Year 1Year 2Year 3Year/QuarterYear/QuarterYear/Quarter9080706050403020101 2 3 4 1 2 3 4 1 24Year 1Year 2Year 3Year/QuarterTime Series Value

a) Excel Procedure: Enter the time series values and quarter values in Excel. Select the column of…

What type of pattern exists in the data? The time series plot shows a trend pattern with no seasonal pattern present. The time series plot shows a trend pattern, but there is also a seasonal pattern in the data. The time series plot shows a horizontal pattern with no seasonal pattern present. The time series plot shows a horizontal pattern, but there is also a seasonal pattern in the data. Use the following dummy variables to develop an estimated regression equation to account for seasor x1 = 1 if quarter 1, 0 otherwise; x2 = 1 if quarter 2, 0 otherwise; x3 = 1 if quarter 3, 0 otherwis

What type of pattern exists in the data? The time series plot shows a trend pattern with no seasonal pattern present. The time series plot shows a trend pattern, but there is also a seasonal pattern in the data. The time series plot shows a horizontal pattern with no seasonal pattern present. The time series plot shows a horizontal pattern, but there is also a seasonal pattern in the data. Use the following dummy variables to develop an estimated regression equation to account for seasor x1 = 1 if quarter 1, 0 otherwise; x2 = 1 if quarter 2, 0 otherwise; x3 = 1 if quarter 3, 0 otherwis

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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The table below contains the average price paid for a new home in a certain area from 2000 to 2010. a. Construct a time-series plot of new home prices. b. What pattern, if any, is present in the data? Year Average_Price_($_thousands)2000 351.12001 330.52002 310.52003 296.72004 229.72005 182.32006 154.52007 156.32008 154.72009 154.52010 154.5
Consider the following time series data Month 1 2 3 4 5 6 7 8 9 10 11 12 Value 80 82 84 83 83 84 85 84 82 83 84 83 a) Construct a time series plot in Excel. Label the axes and graph. b) Develop a three month moving average forecast. Compute MSE and a forecast for month 13. c) Develop an exponential smoothing forecast with a = 0.35. Compute MSE and a forecast for month 13.
The following data set provides the total number of shipments of core major household appliances in the U.S. from 2000 to 2016 (in millions): Year Shipments (millions) 2000 38.4 2001 38.2 2002 40.8 2003 42.5 2004 46.1 2005 47.0 2006 46.7 2007 44.1 2008 39.8 2009 36.5 2010 38.2 2011 36.0 2012 35.8 2013 39.2 2014 41.5 2015 42.9 2016 44.7 a. Plot the time series. b. Fit a three-year moving average to the data and plot the results. c. Fit a five-year moving average to the data and plot the results. d. Compute a linear trend forecasting equation and plot the trend line. e. Compute a quadratic trend forecasting equation and plot the results.
The Hungry Person restaurant has posted its sales (in thousands of dollars) for the last two years. Month 1st Year 2nd Year January 201 216 February 216 223 March 232 240 April 201 244 May 221 232 June 213 220 July 220 211 August 214 213 September 202 217 October 217 220 November 224 212 December 236 216 a) Construct a time series plot in excel. (Label axes and graph) b) Develop a four month moving average. Compute MSE and forecast the amount of sales for the next month. c) Use α = 0.2 to compute the exponential smoothing values. Compute MSE and forecast for the next month. d) Compare the result for the four month average and exponential smoothing. Which appears to provide a better forecast based on MSE? Explain.
#4) Commuter ridership in Athens, Greece, during the summer months is believed to be heavily tied to the number of tourists visiting the city. During the past 12 years, the data are given in the following table. Year Number of Tourists (millions) Ridership (hundreds of thousands) 1 6 11 2 11 16 3 8 16 4 10 14 5 19 28 6 18 26 7 16 21 8 20 25 9 24 45 10 18 28 11 11 18 12 19 35 a) Create a time series plot for the ridership. b) Using linear regression to see if using the year is a good predictor for the ridership. What is the regression equation? How accurate is the model? c) Using linear regression to see if using the number of tourists is a good predictor for the ridership. What is the regression equation? How accurate is the model? d) Which linear regression equation is better? What is the expected ridership if 10 million tourists visit the city next year? e) Excel File
The number of users of a certain website (in millions) from 2004 through 2011 follows. Year Period Users (Millions) 2004 1 1 2005 2 5 2006 3 11 2007 4 59 2008 5 146 2009 6 360 2010 7 608 2011 8 846 (a) Construct a time series plot. -A time series plot contains a series of 8 points connected by line segments. The horizontal axis ranges from 0 to 10 and is labeled: Period. The vertical axis ranges from 0 to 900 and is labeled: Millions of Users. The first point is at approximately (1, 850). The rest are plotted from left to right at regular increments of 1 period in a downward, diagonal direction that becomes less steep as period increases. The last point is at approximately (8, 0). -A time series plot contains a series of 8 points connected by line segments. The horizontal axis ranges from 0 to 10 and is labeled: Period. The vertical axis ranges from 0 to 900 and is labeled: Millions of Users. The first point is at approximately (1, 0). The rest are…
The elevation of a lake surface (feet above sea level) varies according to the annual flow of a river that feeds it. A geological survey provided the following data from equally spaced intervals of time over a 15 year period. Time Period Elevation 1 4817 2 4819 3 4824 4 4822 5 4826 6 4831 7 4836 8 4837 9 4839 10 4837 11 4832 12 4827 13 4823 14 4818 15 4817 Make a time-series graph displaying the data.
corporate triple-a bond interest rates for 12 consecutive months follow.9.5 9.3 9.4 9.6 9.8 9.7 9.8 10.5 9.9 9.7 9.6 9.6a. construct a time series plot. What type of pattern exists in the data?
Analyse the time series of the following supermarket sales data and present the results in graphical form, including a forecast for the daily sales in week 5. Supermarket sales (K000) for a particular period Week 1 Week 2 Week 3 Week 4 Monday 22 22 24 26 Tuesday 36 34 38 38 Wednesday 40 42 43 45 Thursday 48 49 49 50 Friday 61 58 62 64 Saturday 58 59 58 58
The weekly demand (in cases) for a particular brand of automatic dishwasher detergent for a chain of grocery stores located in Columbus, Ohio, follows. Week Demand 1 22 2 18 3 23 4 21 5 17 6 24 7 20 8 19 9 18 10 21 (a) Construct a time series plot. -A time series plot contains a series of 10 points connected by line segments. The horizontal axis is labeled Week and ranges from 0 to 10. The vertical axis is labeled Demand (in cases) and ranges from 0 to 30. The points are plotted at regular increments of 1 week starting at week 1 and ending at week 10 and appear to vary randomly between 15 and 25 on the vertical axis. -A time series plot contains a series of 10 points connected by line segments. The horizontal axis is labeled Week and ranges from 0 to 10. The vertical axis is labeled Demand (in cases) and ranges from 0 to 30. The points are plotted at regular increments of 1 week starting at week 1 and ending at week 10. They start on the left around…
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The Energy Information Administration of the U.S. Department of Energy providedtime series data for the U.S. average price per gallon of conventional regular gasolinebetween January 2007 and February 2014 (Energy Information Administration website,March 2014). Use the Internet to obtain the average price per gallon of conventionalregular gasoline since February 2014.a. Extend the graph of the time series shown in Figure 1.1.b. What interpretations can you make about the average price per gallon of conventionalregular gasoline since February 2014?c. Does the time series continue to show a summer increase in the average price pergallon? Explain.