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
Chapter12: Sequences, Series And Binomial Theorem
Section12.3: Geometric Sequences And Series
Problem 12.58TI: What is the total effect on the economy of a government tax rebate of $500 to each household in...
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![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](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fb67374be-bcfa-44c5-8f74-6eaf46e1a0d1%2F3e0334e8-175e-4970-bca0-e20771a44ca6%2Fs18uf3_processed.png&w=3840&q=75)
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
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