Consider the following time series:Quarter Year 1 Year 2 Year 31696660244364636062554798273(a) Choose a time series plot.(i)100806040203.467Period(t)9101112(ii)100806040201 23.467Period (t)101112 Graph (ii)What type of pattern exists in the data? Is there an indication of a seasonal pattern?Horizontal pattern, with seasonality(b) Use a multiple linear regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data: Qtri = 1 if quarter 1, 0 otherwise; Qtrz = 1 if quarter 2, 0 otherwise; Qtr3 = 1 if quarter 3, 0otherwise. For subtractive or negative numbers use a minus sign even if there is a + sign before the blank. (Example: -300)QtriO Otrz +O Qtr3(c) Compute the quarterly forecasts for next year.Year QuarterFt4144344

Answered: Image /qna-images/answer/a289b56a-8448-46d6-b1f6-217100511e11.jpg

Answered: Consider the following time series:…

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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#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 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 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
Which of the following time series forecasting methods would not be used to forecast seasonal data?
1. Consider the following time series: a. Construct a time series plot. What type of pattern exists in the data? b. Use simple linear regression analysis to find the parameters for the line that minimizes MSE for this time series.
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 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…
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?
Using the time series data in the table, respond to the following items. Period Sales 1 $ 615 2 678 3 761 4 710 5 784 6 801 7 852 8 698 9 1,193 10 1,115 11 1,231 12 1,259 13 1,495 14 1,229 15 1,652 16 1,337 17 1,673 18 1,613 d-1. Compute all possible forecasts using a trend forecasting model using simple linear regression? (Round your answers to 3 decimal places.) Period Sales Predicted Sales Absolute Error 1 615 2 678 3 761 4 710 5 784 6 801 7 852 8 698 9 1,193 10 1,115 11 1,231 12 1,259 13 1,495 14 1,229 15 1,652 16 1,337 17 1,673 18 1,613 d-2. What is the MAD? (Round your answer to 3 decimal places.) d-3. What is the trend equation based on the regression analysis? (Round your answers to 3 decimal places.) Sales = __________ + _______________ time…
canton Supplies, inc., is a service firm that employs approximately 100 individuals.Managers of canton Supplies are concerned about meeting monthly cash obligations andwant to develop a forecast of monthly cash requirements. Because of a recent changein operating policy, only the past seven months of data that follow are considered to berelevant.Month 1 2 3 4 5 6 7Cash Required ($1000s) 205 212 218 224 230 240 246a. construct a time series plot. What type of pattern exists in the data?b. Using Minitab or excel, develop a linear trend equation to forecast cash requirementsfor each of the next two months.
Year U.S. Gov’t T-Bills U.K. Common Stocks 2015 0.063 0.150 2016 0.081 0.043 2017 0.076 0.374 2018 0.090 0.192 2019 0.085 0.106 a. Compute the arithmetic mean rate of return and standard deviation of rates of return for the two series, then discuss these two alternative investments regarding their arithmetic average rates of return, their absolute risk, and their relative risk.
For the following time series plots, explain what type of transformation, if any, would make the variance more stable.

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Consider the following time series: Quarter Year 1 Year 2 Year 3 69 66 60 44 36 46 60 62 55 4 79 82 73 (a) Choose a time series plot. (1) 100 80 60 40 20 0 ++ + 1 2 3. 4 6 7 Period (t) 10 11 12 (ii) 100 80 60 40 20 4 5 6 9 10 11 12