The following data show the quarterly sales of a major auto manufacturer for the years 1 through 3. Use multiplicativemethod to answer the following questions.YearQuarterSales16021803190417012002210326042303121022402902603426. The equation for the trend line of yearly sales is F, = 567 + 150t. What is the prediction for the sales in year 4?<1000b.Between 1000 and 1100a.Between 1100 and 1200d. >1200с.27. What is the seasonal index for quarter 4 in year 1?a.<0.8b.Between 0.8 and 0.9с.Between 0.9 and 1.0d. >1.028. What is the average seasonal index for quarter 1?<0.8b. Between 0.8 and 0.9Between 0.9 and 1.0a.с.d. >1.029. What is the sales forecast for quarter 1 in Year 4?a.<230b. Between 230 and 240с.Between 240 and 250d. >25030. What is the sales forecast for quarter 3 in Year 4?a.<300b.Between 300 and 320Between 320 and 340d. >340с.2.

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Answered: method to answer the following…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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For the data in the following table, compute the additive quarterly seasonal forecast model for the number of ice creams sold by the store without trend. Round your values for the coefficients of the model to three decimal places. Answer Forecast= + Quarter 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 Number of Ice Creams 2868 4273 6820 3620 2401 4551 6981 3678 2685 4873 5972 3914 2032 4655 5964 Copy Data DQ₁ + ( DQ₂ + DQ3
The following table shows the percentage of people 25 years and older who have completed four or more years of college. Use the line of best fit (regression line) to predict when (what year) the percentage will reach 49%. Round the slope and y-intercept to four decimal places, if necessary. Year 1985 1990 1995 2000 2005 2010 Percentage 19.4 21.3 23.0 25.6 27.6 29.9
The quarterly sales of a company (in millions of dollars) over the past three years are given in the following table. Quarter 2007 2008 2009 Quarter 14 28 30 1 Quarter 2 Quarter 3 Quarter 4 20 16 36 40 10 14 18 38 12 b. a. Compute the four seasonal factors (Seasonal Indexes). Show all of your computations. The trend for these data is Trend = 20.82 +0.336 t (t represents time, where t-1 for Quarter 1 of 2007 and t-12 for Quarter 4 of 2009). Forecast sales for the first quarter of 2010 using the trend only. Show all of your computations. c. Forecast sales for the first quarter of 2010 using the trend and seasonal indexes and write your answer below. Show all of your computations.
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
1-
The data in the table represents the amount of fish in a pond after a set amount of weeks. Week 0 1 2 3 4 5 Fish 12 17 24 30 35 42 If the data continues the same linear trend, how many fish do you expect to be in the pond on week 7? 48 fish 40 fish 60 fish 54 fish
Compare the two models based on the forecast errors. Which is the appropriate model to use? Why? Seasonally adjusted linear trend Time, Linear Trend Date Quarter Sales lel e le| e e F. 31/03/2016 1. 1 184 222.25 30/06/2016 2 221 274.25 30/09/2016 3 3 241 282.64 31/12/2016 4 4 541 456.64 31/03/2017 1 5 219 207.81 30/06/2017 2 6 297 259.81 30/09/2017 3 7 330 268.2 31/12/2017 4 335 442.2 31/03/2018 9 202 193.37 30/06/2018 10 283 245.37 30/09/2018 3 11 286 253.76 31/12/2018 4 12 377 427.76 31/03/2019 1 13 243 178.93 30/06/2019 2 14 292 230.93 30/09/2019 3 15 131 239.32 31/12/2019 4 16 528 413.32
Example 18.15 The trend equation for annual sales of a product is– Y = 102 + 36 X with 1s January 1990 as origin. (i) Determine the monthly trend equation with 1ª July 1992 as origin. (ii) Compute the trend values of sales in October 1994. st
Below are given the annual production figures (in thousand tonnes) of a fertiliser factory : Year 2011 2012 2013 2014 2015 2016 2017 Production : 70 75 90 91 95 98 100 (1) Fit a straight line trend by the method of least squares and tabulate the trend values. (i) Convert your annual trend equation into a monthly trend equation.
Q27
Obtain the straight line trend equation and tabulate against each year the trend and short term fluctuations : 1997 1998 1996 670 1992 1993 1994 1995 1990 380 Year : 1991 Value : 400 650 720 690 620 950 1040
Desmos | Graphing Calc Year Time (seconds) 1912 82.2 1924 72.4 1932 66.8 1952 66.8 1960 61.2 1968 60.0 1976 55.65 1984 55.92 1992 54.64 2000 53.8 2008 53.1 a. Decide which variable should be the independent variable and which should be the dependent variable. b. Draw a scatter plot of the data. C. Does it appear from inspection that there is a relationship between the variables? Why or why not? d. Find the equation in the form of: y= a + bx. e. Find the correlation coefficient. f. Find the estimated gold medal time for 1932. Find the estimated time for 1984. g. Why are the answers from part f different from the chart values? h. Does it appear that a line is the best way to fit the data? Why or why not? i. Use the least-squares line to estimate the gold medal time for the next Summer Olympics (Assuming they would be in 2020). Do you think that your answer is reasonable? Why or why not? Note that the fastest speed time in recorded history as of 2020 was 51.22 seconds for the 100 meter…

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method to answer the following questions. Year Quarter Sales 1 160 180 3 190 4 170 2 200 210 3 260 4 230 3 1 210 2 240 3 290 4 260 26. The equation for the trend line of yearly sales is F, = 567 + 150t. What is the prediction for the sales in year 4? %3! 1000