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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Consider the following time series data. Choose the correct time series plot. (i) (ii) (iii) (iv) Plot (ii) What type of pattern exists in the data?Horizontal Pattern Develop a three-week moving average for this time series. Compute MSE and a forecast for week 7. If required, round your answers to two decimal places. Week Time SeriesValue Forecast 1 18 2 13 3 16 4 11 fill in the blank 3 5 17 fill in the blank 4 6 14 fill in the blank 5 MSE: fill in the blank 6The forecast for week 7: fill in the blank 7 Use α = 0.2 to compute the exponential smoothing values for the time series. Compute MSE and a forecast for week 7. If required, round your answers to two decimal places. Week Time SeriesValue Forecast 1 18 2 13 fill in the blank 8 3 16 fill in the blank 9 4 11 fill in the blank 10 5 17 fill in the blank 11 6 14 fill in the blank 12 MSE: fill in the blank 13The forecast for week 7: fill in the blank 14
Please answer number 2
Describe the three major categories of data (time-series, cross-sectional, and panel).
What type of variable is required when drawing a time-series plot? Why do we draw time-series plots? A is required when drawing a time-series plot. discrete variable quantitative variable at the interval level continuous variable quantitative variable at the ratio level qualitative variable qualitative variable at the ordinal level categorical variable quantitative variable qualitative variable at the nominal level
A statistical program is recommended. The number of users of a certain website (in millions) from 2004 through 2011 follows. Year Period Users (Millions) 2004 1 1 2005 2 7 2006 3 11 2007 4 57 2008 5 146 2009 6 359 2010 7 609 2011 8 845 (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 doesn't appear to become more or 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.…
Table 7 shows the seasonal factors for a monthly time series: Table 7 Month Seasonal Month Factor January -358.1 May February -196.3 June March 12.5 July April 187.4 August Describe the seasonal variation in this time series. Seasonal Factor 487.2 276.1 -27.9 -124.6 Month September October November December Seasonal Factor -136.7 92.6 70.4 -282.6
Companies are devoting time and energy to promote recycling. A major recycling company found some old documents that present the recorded amount of cell phone collected over a span of eight years. Year Cellular Telephones Collected (in millions) 2009 2.2 2010 2.6 2011 2.9 2012 3.4 2013 3.1 2014 4.2 2015 4.9 2016 5.3 Part a) Develop a time series plot with Year on the X axis and Cellular Telephones Collected on the Y axis. Part b) Does there appear to be a relationship between time and cellular telephones collected?
For each of the below ACF plots which are obtained for a time series data of 4 different variables of interest: a) Explain the ACF plot. b) Describe what the raw data is likely to look like over time. c) What kind of variable is this plot likely to characterise (e.g., stock prices, exchange rates, temperature, etc.)?
Year Quarter Price 2010 1 263600 2010 2 264100 2010 3 259500 2010 4 248900 2011 1 251400 2011 2 259200 2011 3 251400 2011 4 252000 2012 1 272300 2012 2 258600 2012 3 265500 2012 4 291200 2013 1 290500 2013 2 302400 2013 3 322900 2013 4 331000 2014 1 324700 2014 2 344400 2014 3 327500 2014 4 355400 2015 1 347200 2015 2 341000 2015 3 330800 2015 4 370300 2016 1 350800 2016 2 380000 2016 3 368600 2016 4 371100 2017 1 372500 2017 2 386300 2017 3 385500 2017 4 409700 2018 1 408000 2018 2 423400 2018 3 404300 Predictive Analytics: Time-Series Forecasting: The above contains data on median home prices in the West Census region quarterly from 2010 to2018. Easter Realtor, Inc. is interested in houses in this region. They want to use this data toforecast home price in the fourth quarter of 2018. For cross-validation, use the training set fromthe first quarter of 2010 to the fourth quarter in 2016, and use a validation set…
Consider the following time series data. Month 1 2 3 4 5 6 7 Value 25 14 21 13 20 24 16 (a) Construct a time series plot. -A time series plot contains a series of 7 points connected by line segments. The horizontal axis ranges from 0 to 8 and is labeled: Month. The vertical axis ranges from 0 to 30 and is labeled: Time Series Value. The points are plotted from left to right at regular increments of 1 month starting at month 1. The points appear to vary randomly between 8 to 20 on the vertical axis. The plot reaches its maximum time series value at month 1. -A time series plot contains a series of 7 points connected by line segments. The horizontal axis ranges from 0 to 8 and is labeled: Month. The vertical axis ranges from 0 to 30 and is labeled: Time Series Value. The points are plotted from left to right at regular increments of 1 month starting at month 1. The points appear to vary randomly between 8 to 20 on the vertical axis. The plot reaches its maximum time…
Consider the following time series data: Month 1 2 3 4 5 6 7 Value 23 15 20 12 18 22 15 (a) Choose the correct time series plot. (i) (ii) (iii) (iv) What type of pattern exists in the data? (b) Develop a three-month moving average for this time series. Compute MSE and a forecast for month 8. If required, round your answers to two decimal places. Do not round intermediate calculation. MSE: The forecast for month 8: (c) Use α = 0.2 to compute the exponential smoothing values for the time series. Compute MSE and a forecast for month 8. If required, round your answers to two decimal places. Do not round intermediate calculation. MSE: The forecast for month 8: (d) Compare the three-month moving average forecast with the exponential smoothing forecast using α = 0.2. Which appears to provide the better forecast based on MSE? (e) Use trial and error to find a value of the exponential smoothing…
Consider the following time series data. Month 1 2 3 4 5 6 7 Value 23 12 19 11 18 22 14 (a) Construct a time series plot. A time series plot contains a series of 7 points connected by line segments. The horizontal axis ranges from 0 to 8 and is labeled: Month. The vertical axis ranges from 0 to 30 and is labeled: Time Series Value. The points are plotted from left to right at regular increments of 1 month starting at month 1. The points appear to vary randomly between 6 to 18 on the vertical axis. The plot reaches its maximum time series value at month 1. A time series plot contains a series of 7 points connected by line segments. The horizontal axis ranges from 0 to 8 and is labeled: Month. The vertical axis ranges from 0 to 30 and is labeled: Time Series Value. The points are plotted from left to right at regular increments of 1 month starting at month 1. The points appear to vary randomly between 11 to 23 on the vertical axis. The plot reaches its maximum time…

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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