llustration 12.12. Fit a trend line by the method of four yearlymoving averages to the following time series data:Production of sugar in IndiaYearProduction(in lakhs of tonnes)YearProduction19445195110194519529.19461953101947195411194819551119491950S677 689

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Answered: fllustration 12.12. Fit a trend line by…

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 data: Monthly Profit of a Gym Feb-12 Mar-12 Apr-12 May-12 Jun-12 Jul-12 Aug-12 Sep-12 6,090 Month Jan-12 Profit ($) 6,500 6.253 5,514 5,357 5,425 6,278 8,119 6,390 Step 3 of 5: Determine the exponentially smoothed forecast for the next time period using a smoothing constant, a, of 0.35. If necessary, round your answer to one decimal place.
The following is the data of the production of corona vaccine (Pfizer) for last few months. Using the moving average of 5 months determine the trend of production of corona vaccine. Month February March April Мay June July Production (units) 400 600 500 600 700 600 O a. 560 and 600 O b. 450 and 550 O C. 500 and 600 O d. 500 and 560
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The quarterly earnings of a large soft drink company have been recorded for the period 2014 - 2017. These data (in millions of rupees) are shown in the accompanying table. Year Quarter Sales Centered moving average 2014 1 52 2 67 3 85 62.03 4 54 63.38 2015 1 57 66.63 2 75 65.16 3 90 67.99 4 61 70.94 2016 1 60 70.55 2 77 73.61 3 94 71.57 4 63 72.84 2017 1 66 73.68 2 82 76.02 3 98 4 67 Find the seasonal index values using the moving averages. The trend line with de-seasonalised series was found as: Y = 62.09 + 1.14t where t is the quarter number ( t=1 for the first quarter 2014). Find the forecasted sales for the four quarters of year 2017.
Consider the following data: Month Jan-14 Feb-14 Profit ($) 16,113 16,263 Monthly Profit of an Auto Repair Shop Mar-14 Apr-14 May-14 Jun-14 Jul-14 Aug-14 Sep-14 15,055 17,117 18,763 17,210 19,141 18,468 20,254 Step 3 of 4: Determine the exponential smoothing forecast for the next time period using a smoothing constant of 0.35. If necessary, round your answer to one decimal place.
From the data given below, using the simple average of price relative comput: (i) Index number for 1998 with 1995 as the base and (ii) Index number for 1995 with 1998 as the base. Comment upon the result, if any. Price Items Unit 1995 1998 6. Rice Dal Ghee kg kg kg 15 20 40 50
Given the following data, calculate the three-month moving average forecasts formonths 4, 5, 6, and 7
Using the table below, what is your forecast for week 11 using a three-week weighted moving average with weights of 0.30 for the most current time period and 0.2 for the oldest time period? Week Sales 1 110 115 125 4 120 5 125 120 7 130 8. 115 9. 110 10 130 2.
Q3. Consider the following data. Period Rate of Return (%) 1 -6.0 2 -8.0 3 -4.0 4 2.0 5 5.4 What is the mean growth rate over these five periods?
Month Actual demand Forecasted Demand 1 950 1000 2 1070 1000 3 1100 1000 4 960 1000 5 1090 1000 6 1050 1000 For the dataset above, compute the overall MAPE.
12. Fit a straight line trend by the method of least squares to the following data. Assuming that the same rate of change continues, what would be the predicted earming for the year 2015? Year 2001 2002 2003 2004 2005 2006 2007 2008 Eamings (Rs. lakh): Do not plot the trend values on the graph. 38 40 65 72 69 60 87 95
Mlustration 12. From the following data compute the 3-yearly and 5-yearly moving averages and: Year : 1 3 4 7 8 9. 10 11 Values : 25 30 34 37 39 40 40 39 37 34 30

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fllustration 12.12. Fit a trend line by the method of four yearly moving averages to the following time series data: Production of sugar in India Year Production(in lakhs of tonnes) Year Production 1944 5 1951 10 1945 6. 1952 1946 1953 10 1947 7 1954 11 1948 1955 11 1949 1950 6.