**Exhibit 17-4**The Espresso Cart has had the following pattern of espresso sales over the last two weeks:| | Week 1 | | | Week 2 | ||--------|--------|--------|--------|--------|--------|| Monday | 873 | | Monday | 912 || Tuesday| 904 | | Tuesday| 859 || Wednesday | 911 | | Wednesday | 906 || Thursday | 887 | | Thursday | 900 || Friday | 899 | | Friday | ? |Refer to Exhibit 17-4. What is the forecast for Friday's sales using a three-day weighted moving average with weights of 0.5 (for newest), 0.3, and 0.2 (for oldest)?- a. 881.3- b. 894.7- c. 889.4- d. 893.6

The espresso Cart has had the following pattern of espresso sales over the last two weeks:Week 1Week…

Answered: Exhibit 17-4 The Espresso Cart has had…

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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Illustration 13.15. Construct the index no. of business activity from the following data using (a) A.M. and (b) G.M. Item Weight Index Industrial Production 36 30 Mineral Production 7 135 Internal Trade 24 200 Financial Activity 20 135 Exports and Imports Shipping Activity 7 325 6. 300
What type of correlation is exhibited by the following graph? Independent Variable a. Positive Correlation b. No Correlation c. Negative Correlation d. Either positive or negative correlation Dependent Variable
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.
Perdisco Limited has shared their annual sales revenue over the last 6 financial years from 2010 to 2015. Year Sales ($ 000) 2010 4500 2011 5100 2012 4900 2013 5400 2014 5670 2015 6000 Using linear trend equation forecast the sales revenue of Perdisco Limited for 2016. Calculate the forecasted sales difference if you use 3-period weighted moving average designed with the following weights: 2013 (0.1), 2014 (0.3) and 2015(0.6). Please answer this question. this is not graded question. this is from book which is provided by my teacher for understanding concepts. Please solve this as i have finding difficulty in solving.
1. Give below is the data on production of a company (in lakhs). Year: 1983 1984 1985 1986 1987 1988 1989 Production: 15 14 18 20 17 24 27 Fit the linear trend. Compute the trend values for each year. Estimate the production for уear 1991.
Give typed full explanation
A small detergent company in Karachi is confident that their sales are growing significantly week by week. Treating sales for the previous eight weeks as a typical example of this increasing trend, they recorded them in PKR 1000's and examined the results. Week 1 2 3 4 5 6 Sales (in PKR) 2.59 2.55 2.63 2.68 2.74 2.83 2.86 2.99 a) Plot a scatter diagram between week and sales. b) Find the equation of regression line. c) Find the expected sales for 12 week d) Find the correlation coefficient between the two variables.
am. 13.
I just need the 2 bottom ones (:
4. Draw a line / curve of best fit for the following sets of data & identify if they are linear, quadratic or exponential: 2500 1500 1000 500 300 200 -100 25 50
Illustration 54. From the following data relating to the average quarterly prices of a commodity obtain the scasonal indices by the method given by prof. Pearson. Also comment on the seasonal indices. Average Quarterly Prices of a Commodity Qrs. II III IV Yr. 1994 30 26 22 31 1995 35 28 22 36 1996 31 29 28 32 25 35 31 36 1997 31 26 33 1998 34

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