Maurice Tutor

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About Maurice Tutor

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Expertise:
Algebra,Applied Sciences See all
Algebra,Applied Sciences,Biology,Calculus,Chemistry,Economics,English,Essay writing,Geography,Geology,Health & Medical,Physics,Science Hide all
Teaching Since: May 2017
Last Sign in: 398 Weeks Ago, 1 Day Ago
Questions Answered: 66690
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Education

  • MCS,PHD
    Argosy University/ Phoniex University/
    Nov-2005 - Oct-2011

Experience

  • Professor
    Phoniex University
    Oct-2001 - Nov-2016

Category > Management Posted 07 Jul 2017 My Price 15.00

attachment is Problem

Please find attached 2 documents. One attachment is Problem 26 and the other attachment is the Solutions printed in the back of the text for Problem 26. I have not been able to reach the same solutions for 26 B. C. and D. Would you be able to show me the Step by Step process to achieve the answers? It is my understanding this is done using the Excel application and the LINEST Function to find the regression. I just can not come up with the same numbers as what is listed for the equation: Value = 2491.67 - 711.67 Qtr1 - 1511.67 Qtr2 + 326.67 Qtr 3 which is printed in the Solution for 26b. OR any of the other numbers in Solutions c. and d.PROBLEM Facts Known:  The quarterly sales data (number of copies sold) for a college textbook over the past three years  are as follows:

Quarter Year 1 Year 2 Year 3

      1  1690  1800  1850

      2    940    900  1100

      3  2625  2900  2930

      4  2500  2360  2615

 

 

 

b.)  Use a regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data.  Qtr1 = 1 if Quarter 1, 0 otherwise; Qtr2 = 1 if Quarter 2, 0 otherwise; Qtr3 = 1 if Quarter 3, 0 otherwise.

 

 

 

Compute the quarterly forecasts for next year.

 

Let t = 1 to refer to the observation in quarter 1 of year 1; t = 2 to refer to the observation in quarter 2 of year 1, … ; and t = 12 to refer to the observation in quarter 4 of year 3.  Using dummy variables defined in part (b) and also using t, develop an equation to account for seasonal effects ad any linear trend in the time series.  Based upon the seasonal effects in the data and linear trend, compute the quarterly forecasts for next year.

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Maurice Tutor
(5)
Status NEW Posted 07 Jul 2017 12:07 PM My Price 15.00

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