Homework Help is Here – Start Your Trial Now!
Math
Statistics
A construction company builds permanent docks and seawalls along the southern shore of Long Island, New York. Although the firm has been in business only five years, revenue has increased from $298,000 in the first year of operation to $1,074,000 in the most recent year. The following data show the quarterly sales revenue in thousands of dollars. Quarter Year 1 Year 2 Year 3 Year 4 Year 5 1 15 32 70 87 171 2 105 141 160 207 287 3 170 240 321 379 440 4 8 21 43 77 176 (a) Construct a time series plot. What type of pattern exists in the data? O The time series plot shows only seasonal effects. The time series plot shows only a linear trend. O The time series plot shows neither a linear trend nor seasonal effects. O The time series plot shows both a linear trend and seasonal effects. (b) Use the following dummy variables to develop an estimated regression equation for the time series data (in $1,000s) to account for seasonal effects in the data. x, 1 if quarter 1, 0 otherwise; x = 1 if quarter 2, 0 otherwise; x = 1 if quarter 3, 0 otherwise. (c) Based on the model you developed in part (b), compute estimates of quarterly sales (in $1,000s) for year 6. quarter 1 forecast quarter 2 forecast quarter 3 forecast $ quarter 4 forecast thousand thousand thousand thousand (d) Lett 1 refer to the observation in quarter 1 of year 1; t = 2 refer to the observation in quarter 2 of year 1;... and t = 20 refer to the observation in quarter 4 of year 5. Using the dummy variables defined in part (b) and t, develop an estimated regression equation for the time series data (in $1,000s) to account for seasonal effects and any linear trend in the time series. (Round your numerical values to one decimal place.) 6:09 PM

A construction company builds permanent docks and seawalls along the southern shore of Long Island, New York. Although the firm has been in business only five years, revenue has increased from $298,000 in the first year of operation to $1,074,000 in the most recent year. The following data show the quarterly sales revenue in thousands of dollars. Quarter Year 1 Year 2 Year 3 Year 4 Year 5 1 15 32 70 87 171 2 105 141 160 207 287 3 170 240 321 379 440 4 8 21 43 77 176 (a) Construct a time series plot. What type of pattern exists in the data? O The time series plot shows only seasonal effects. The time series plot shows only a linear trend. O The time series plot shows neither a linear trend nor seasonal effects. O The time series plot shows both a linear trend and seasonal effects. (b) Use the following dummy variables to develop an estimated regression equation for the time series data (in $1,000s) to account for seasonal effects in the data. x, 1 if quarter 1, 0 otherwise; x = 1 if quarter 2, 0 otherwise; x = 1 if quarter 3, 0 otherwise. (c) Based on the model you developed in part (b), compute estimates of quarterly sales (in $1,000s) for year 6. quarter 1 forecast quarter 2 forecast quarter 3 forecast $ quarter 4 forecast thousand thousand thousand thousand (d) Lett 1 refer to the observation in quarter 1 of year 1; t = 2 refer to the observation in quarter 2 of year 1;... and t = 20 refer to the observation in quarter 4 of year 5. Using the dummy variables defined in part (b) and t, develop an estimated regression equation for the time series data (in $1,000s) to account for seasonal effects and any linear trend in the time series. (Round your numerical values to one decimal place.) 6:09 PM

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
See similar textbooks
icon
Related questions
Question
i need the answer quickly
A construction company builds permanent docks and seawalls along the southern shore of Long Island, New York. Although the firm has been in business only five years, revenue has increased from $298,000 in the first year of operation to $1,074,000 in the most recent year. The following data show the quarterly sales revenue in thousands of dollars. Quarter Year 1 Year 2 Year 3 Year 4 Year 5 1 15 32 70 87 171 2 105 141 160 207 287 3 170 240 321 379 440 4 8 21 43 77 176 (a) Construct a time series plot. What type of pattern exists in the data? O The time series plot shows only seasonal effects. The time series plot shows only a linear trend. O The time series plot shows neither a linear trend nor seasonal effects. O The time series plot shows both a linear trend and seasonal effects. (b) Use the following dummy variables to develop an estimated regression equation for the time series data (in $1,000s) to account for seasonal effects in the data. x, 1 if quarter 1, 0 otherwise; x = 1 if quarter 2, 0 otherwise; x = 1 if quarter 3, 0 otherwise. (c) Based on the model you developed in part (b), compute estimates of quarterly sales (in $1,000s) for year 6. quarter 1 forecast quarter 2 forecast quarter 3 forecast $ quarter 4 forecast thousand thousand thousand thousand (d) Lett 1 refer to the observation in quarter 1 of year 1; t = 2 refer to the observation in quarter 2 of year 1;... and t = 20 refer to the observation in quarter 4 of year 5. Using the dummy variables defined in part (b) and t, develop an estimated regression equation for the time series data (in $1,000s) to account for seasonal effects and any linear trend in the time series. (Round your numerical values to one decimal place.) 6:09 PM
Transcribed Image Text:A construction company builds permanent docks and seawalls along the southern shore of Long Island, New York. Although the firm has been in business only five years, revenue has increased from $298,000 in the first year of operation to $1,074,000 in the most recent year. The following data show the quarterly sales revenue in thousands of dollars. Quarter Year 1 Year 2 Year 3 Year 4 Year 5 1 15 32 70 87 171 2 105 141 160 207 287 3 170 240 321 379 440 4 8 21 43 77 176 (a) Construct a time series plot. What type of pattern exists in the data? O The time series plot shows only seasonal effects. The time series plot shows only a linear trend. O The time series plot shows neither a linear trend nor seasonal effects. O The time series plot shows both a linear trend and seasonal effects. (b) Use the following dummy variables to develop an estimated regression equation for the time series data (in $1,000s) to account for seasonal effects in the data. x, 1 if quarter 1, 0 otherwise; x = 1 if quarter 2, 0 otherwise; x = 1 if quarter 3, 0 otherwise. (c) Based on the model you developed in part (b), compute estimates of quarterly sales (in $1,000s) for year 6. quarter 1 forecast quarter 2 forecast quarter 3 forecast $ quarter 4 forecast thousand thousand thousand thousand (d) Lett 1 refer to the observation in quarter 1 of year 1; t = 2 refer to the observation in quarter 2 of year 1;... and t = 20 refer to the observation in quarter 4 of year 5. Using the dummy variables defined in part (b) and t, develop an estimated regression equation for the time series data (in $1,000s) to account for seasonal effects and any linear trend in the time series. (Round your numerical values to one decimal place.) 6:09 PM
Expert Solution
trending now

Trending now

This is a popular solution!

steps

Step by step

Solved in 5 steps with 27 images

SEE SOLUTIONCheck out a sample Q&A here
Blurred answer
Recommended textbooks for you
MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman
SEE MORE TEXTBOOKS