1) Raj collected the following data on the quarterly room occupancy (in hundreds) for a resort hotel in lowa.Year quarter Occupancy2014 12342015 123st42016 12342017 12342018 12341621918152010181724132217251121182614251. Plot the data and describe any trend and seasonal effects you observe in the data.1. Compute and interpret the seasonal indices.1. Forecast the occupancy for four quarters of 2019.

Given the data of quarterly room occupancy for a resort hotel in Lowa as Year quarter Occupancy…

Answered: 1) Raj collected the following data on…

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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18. Fit a straight line trend for the following data. 1997 1996 1998 1999 2000 Year: Per capita: 25 30 32 37 40 (Consumption of cotton in Kgs) Estimate the per capita consumption for the year 2002. Represent the trend line graphi- cally. CS Scanned with CamScanner
Try to fit any two moving averages models to the following data and discuss its performance. YEAR 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 QUANTITY 21 22 23 25 24 22 25 26 27 26
What are the advantages of multiplicative model .
The table below lists the percent of a country's population that is foreign-born for selected years. Year 1930 1940 1950 6.7 1960 1970 5.3 1980 1990 2000 2008 Percent 11.4 8.5 4.6 6.5 8.1 10.2 12.3 Answer parts a through e. (a) Plot the data. Let x =0 correspond to the year 1930, x= 10 correspond to 1940, and so on. Choose the correct graph below. OA. B. Oc. OD. Q (0, 80,101 by (0,15,3] (b) Find a quadratic function f(x) = a(x-h) +k that models the data. Use (40,4.6) as the vertex and (20,6.7) as the other point to determine a. f(x) = (Use integers or decimals for any numbers in the expression. Type an integer or decimal rounded to four decimal places as needed.)
Provide an appropriate graph for the given data
A company has the following monthly sales for the past year. Plot the data points on a line graph and describe the results. Month Sales 1 145 2 146 3 145 4 150 5 148 6 150 7 156 8 160 9 158 10 153 11 152 12 154
For the data set, perform exponential smoothing with alpha = 0.1 to determine the forecast for week 20. week Sales (1000s of gallons) 1 17 2 21 3 19 4 23 5 18 6 16 7 20 8 18 9 22 10 20 11 15 12 22 13 31 14 34 15 31 16 33 17 28 18 32 19 30
Example 3: Using three-year moving averages, determine the trend. Production Production Year Year (1000 tonnes) (1000 tonnes) 1990 21 1995 22 1991 22 1996 25 1992 23 1997 26 1993 25 1998 27 1994 24 1999 26
Monday Tuesday Wednesday Thursday Friday Week 1 55 40 33 20 70 Week 2 60 48 50 36 63 Week 3 58 44 38 50 72 Week 4 80 40 40 30 64 Instructions: The table above, which shows income (in thousands of dollars) from sales of a particular product over a four week period. Determine the seasonal variation each of the week Hence calculate the average seasonal variation for each day of the week Plot the graph of the original data and then add the trend line obtained using the moving averages Comment briefly on the trend observed on the graph and calculate the sales figure that is likely to be achieved for the next Monday using the trend line
The following data show the quarterly sales of a major auto manufacturer for the years 1 through 3. Use multiplicative method to answer the following questions. Year Quarter Sales 160 2 180 3 190 4 170 1 200 2 210 3 260 4 230 3 1 210 2 240 290 260 3 4 26. The equation for the trend line of yearly sales is F, = 567 + 150t. What is the prediction for the sales in year 4? 1200 с. 27. What is the seasonal index for quarter 4 in year 1? a. 1.0 28. What is the average seasonal index for quarter 1? 1.0 29. What is the sales forecast for quarter 1 in Year 4? a. 250 30. What is the sales forecast for quarter 3 in Year 4? a. 340 с. 2.
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
Fit a trend function y = A. B* to the following data. 2 3 4 5 y : 1.6 4.5 13.8 40 2 125.0

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