Business at Tina's Floral Shop can be viewed as falling into three distinct seasons: (1) Christmas (November andDecember); (2) Mother's Day (late April to May); and (3) all other times. Time Series Analysis and Forecasting of Averageweekly sales ($) during the past four years are shown below:t123456789101112131415InterceptSalesQuarterly Sales Data for Tina's Floral ShopYearYear 1Year 2Year 3Year 4Year 5Quarter1231231231Sales (1000s) (Y₂)1769.01925.0789.01889.02098.0990.02140.02294.01009.02156.02378.01086.023123Coefficients1448.50153934.39781177Show Transcribed TextCMA(3)1494.331534.331592.001659.001742.671808.001814.331819.671847.671873.33Forecasts -->a) Find the missing St* It. (Show Calculation)b) Find the missing St. (Show Calculation)c) Complete the Forecast for Year 5. (Show Calculation)St ItStDeasonalized(Y₁/S₂)1500.401513.781446.101602.181649.831814.491815.071803.961849.321828.641870.021990.44Trend Forecast1482.901517.301551.691586.091620.491654.891689.291723.681758.081792.481826.881861.28Forecast1748.371929.47846.621870.042060.69902.921991.702191.92959.222113.372323.141015.53

Given the data as t Year Quarter Sales (1000s) (Yt) CMA(3) St*It St Deasonalized (Yt/St) Trend…

Answered: Business at Tina's Floral Shop can be…

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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Boran Stockbrokers, Inc., selects four stocks for the purpose of developing its own index of stock market behavior. Prices per share for a year 1 base period, January year 3, and March year 3 follow. Base-year quantities are set on the basis of historical volumes for the four stocks. Price per Share ($) Year 1 Stock Industry Quantity Year 1 March January Year 3 Base Year 3 A Oil 100 29.50 24.75 22.50 Computer 150 65.00 49.00 47.50 Steel 75 40.00 31.00 29.50 D Real Estate 50 18.00 6.50 3.75 Compute the price relatives for the four stocks making up the Boran index. (Round your answers to one decimal place.) Price Relative Stock January March A 2475.0 2250.0 B 7350.0 7125.0 2325.0 2212.5 D 325.0 187.5 Use the weighted average of price relatives to compute the January year 3 and March year 3 Boran indexes. (Round your answers to one decimal place.) IJan = 75.2 IMar = 70.9
Management at Jagoda Wholesalers, in Calgary, Canada, has used time-series regression based on point-of-sale data to forecast sales for the next 4 quarters. Sales estimates are $100,000, $120,000, $140,000, and $160,000 for the respective quarters. Seasonal indices for the four quarters have been found to be1.30, .90, .70, and 1.10, respectively.
The problem is based on the following data given. Observations of the demand for a certain part stocked at a parts supply depot during the calendar year 2013 were ( as shown ). What would an MA(1) forecasting method mean? Compare the accuracy of MA(1) and MA(4) forecasts for July through December 2013.
Forecasting Methods: Perform Trend Series Analysis (sales projection for the year 10, 12 and 17) Make based on the sales data below:Year 1: 24,333; Year 2: 33,524; Year 3: 26,778; Year 4: 30,567; Year 5: 27,564; Year 6: 24,555; Year 7: 21,777 and Year 8: 25,669.
Suppose a firm has had the following historic sales figures. Year: 2016 2017 2018 2019 2020 Sales $2,570,000 $3,750,000 $4,380,000 $5,010,000 $5,520,000 What would be the forecast for next year’s sales using regression to estimate a trend?
The following time series shows the sales of supermarket chain over the last six months. Month Sales ($ 000) August 2021 250 Sep 2021 280 Oct 2021 295 Nov 2021 320 Dec 2021 380 Jan 2022 360 Develop a linear trend equation that can be used to forecast sales in Feb 2022. Forecast the sales in Feb 2021 using a three-period weighted moving average designed with the following weights: Nov 2021 weight 0.6, Dec 2021 weight 0.3 and Jan 2022 weight 0.1. Which method (A or B) is the best? Explain why.
47. Given the following data : Weekly take-home pay (wages) Consumer price index Year 109.50 112.8 2012 2013 112.20 118.2 2014 116.40 127.4 2015 125.08 138.2 2016 135.40 143.5 2017 138.10 149.8 () What was the real average weekly wage for each year ? (i) In which year did the employees have the greatest buying power ? (ii) What percentage increase in the weekly wages for the year 2017 is required (if any) to provide the same buying power that the employees enjoyed in the year in which they had the highest real wages ?
The Northwoods Outdoor Company is a catalog sales operation that specializes in outdoor recreational clothing. Demand for its items is very seasonal, peaking during the Christmas season and during the spring. It has accumulated the following data for orders per season (quarter) during the past 5 years: a. Develop a seasonally adjusted forecast model for these order data. Forecast demand for each quarter for year 6 (using a linear trend line forecast estimate for orders in year 6). b. Develop a separate linear trend line forecast for each of the four seasons and forecast each season for year 6. c. Which of the two approaches used in (a) and (b) appears to be the more accurate? Use MAD to verify your selection.
Based on the following graph, what is the year when the largest decrease in GDP took place ? GDP (change YoY) 6% 5% 4% 4% 3% 3% 3% 3% 2% 2% 1% -1% -1% -8% 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010o 2011 2012 2013 2009 2001 2005 2007
For the past 10 years, you have been observing the sales of your company since you embarked on an aggressive advertising campaign. You have been recording the amounts spent on advertising and the corresponding sales as follows: Year Advert (X) Sales (Y) 2001 10 44 2002 9 40 2003 11 42 2004 12 46 2005 11 48 2006 12 52 2007 13 54 2008 13 58 2009 14 56 2010 15 60 You would like to determine whether a relationship exists between your two variables of interest and therefore decide to run a regression. Specify the estimation model you will use (the econometric form). Identify the independent and the dependent variables. Use an econometric package of your choice (EViews, SPSS, STATA etc) to estimate the model. From the regression output, report the coefficients, standard errors, t-statistics, probability and R-squared (report the results in a table). Re-write the specified model in (a) with values…
An entrepreneur who owns and operates two businesses (A and B) would like to analyze their profitability. They would like your help in the analysis. They give you the annual net profit (in thousands of $) for each business from 2008-2020. Table 1: Annual Net Profits for Businesses A and B Business Year Profit Business Year Profit 2008 -50 2008 -10 2009 57 2009 30 2010 71 2010 27 2011 64 2011 22 2012 60 2012 21 2013 50 2013 20 A 2014 41 2014 24 2015 59 2015 24 2016 71 2016 32 2017 71 2017 36 2018 74 2018 37 019 81 20 40 2020 97 2020 49 a. Suppose you want to graph the distribution of profits. Explain why using only one stem- plot might not be optimal for the analysis. b. Describe the correct stemplot to use. Generate this stemplot. Explain your steps. What can you say about the distribution from this stemplot? c. When are stemplots useful? And why is that? d. Suppose that instead of having 26 observations you have 200 observations. What graph should you generate? e. What other type of…

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