The following is the list of MAD statistics for each of the models you have estimated...
The following is the list of MAD statistics for each of the models you have estimated from time-series data:
| Model | MAD |
| Linear Trend | 1.38 |
| Quadratic Trend | 1.22 |
| Exponential Trend | 1.39 |
| AR(2) | 2.71 |
Based on the MAD criterion, the most appropriate model is
Question 12 options:
|
A. linear trend. |
|
|
B. quadratic trend. |
|
|
C. exponential trend. |
|
|
D. AR(2). |
Homework Answers
since MAD is least for the Quadratic trend , therefore
Based on the MAD criterion, the most appropriate model is Quadratic trend
option B is correct
Add Answer to:
The following is the list of MAD statistics for each of the
models you have estimated...
The accompanying data file contains 20 observations for t and yt. Actual series are plotted along with the superimposed linear and exponential trends. t y t y t y t y 1 1.91 6 4.93...
The accompanying data file contains 20 observations for
t and yt.
Actual series are plotted along with the superimposed linear and
exponential trends.
t
y
t
y
t
y
t
y
1
1.91
6
4.93
11
5.96
16
15.58
2
3.57
7
6.78
12
9.02
17
12.33
3
5.83
8
4.58
13
9.52
18
13.95
4
5.39
9
7.19
14
14.02
19
15.63
5
2.78
10
8.81
15
14.57
20
19.77
The accompanying data file contains 20 observations for tand...
The accompanying data file contains 20 observations for tand yt: Click here for the Excel Data...
The accompanying data file contains 20 observations for tand yt: Click here for the Excel Data File Actual series are plotted along with the superimposed linear and exponential trends. 25 20 15 • Y 10 Linearly Expon. (v) 5 0 0 10 15 20 25 b-1. Estimate a linear trend model and an exponential trend model for the sample. (Round your answers to 2 decimal places.) Exponential Trend Variable Intercept Linear Trend 0.43 0.84 0.10 Standard Error b-2. Calculate the...
Consider the following estimated trend models. Use them to make a forecast for t=20. a. Linear...
Consider the following estimated trend models. Use them to make a forecast for t=20. a. Linear Trend: ŷ = 14.32 +0.75t (Round Intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.) b. Quadratic Trend: y - 17.78 +0.94 - 0.01 2 decimal places.) (Round Intermediate calculations to at least 4 decimal places and final answer to c. Exponential Trend: In(y) - 1.9.0.076 to 2 decimal places.) -0.02 (Round Intermediate calculations to at least 4...
Consider the following estimated trend models. Use them to make a forecast for t= 24. a....
Consider the following estimated trend models. Use them to make a forecast for t= 24. a. Linear Trend: = 11.64 + 1.04t (Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.) Ў b. Quadratic Trend: û = 19.26 + 0.88t - 0.0172 (Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.) 9 c. Exponential Trend: In(y) = 2.4 +0.06t, se = 0.01 (Round intermediate calculations to...
Consider the following sample regressions for the linear, the quadratic, and the cubic models along with...
Consider the following sample regressions for the linear, the quadratic, and the cubic models along with their respective R2 and adjusted R2. Linear Quadratic Cubic Intercept 9.66 10.00 10.06 x 2.66 2.75 1.83 x2 NA −0.31 −0.33 x3 NA NA 0.26 R2 0.810 0.836 0.896 Adjusted R2 0.809 0.833 0.895 a. Predict y for x = 1 and 2 with each of the estimated models. (Round intermediate calculations and final answers to 2 decimal places.) b. Select the most appropriate...
Consider the following sample regressions for the linear, the quadratic, and the cubic models along with...
Consider the following sample regressions for the linear, the quadratic, and the cubic models along with their respective R2 and adjusted R2. Intercept х x2 Linear 28.53 0.12 NA NA Quadratic 28.80 0.01 0.01 Cubic 28.62 0.15 -0.02 -0.01 x3 NA R2 Adjusted R2 0.005 -0.021 0.006 -0.048 0.006 -0.077 a. Predict y for x = 2 and 4 with each of the estimated models. (Round intermediate calculations to at least 4 decimal places and final answers to 2 decimal...
Models with quadratic terms: Using data from a random sample of 305 women, we have estimated the ...
Models with quadratic terms: Using data from a random sample of 305 women, we have estimated the following model that relates a woman's sleep time in a week (in minutes) to her work time (in minutes) and age. SLEEP4206.17 -0.13 WRK- 37.64 AGE+0.47 AGE (333.60)(0.03) (17.46) (0.21) n - 305, R-0.092 (a) Explain the insights that the regression results provide for the effect of age on sleep, all else equal. In particular, all else equal, at what age women are...
Check my work 4 Click here for the Excel Data File Actual series are plotted along...
Check my work 4 Click here for the Excel Data File Actual series are plotted along with the superimposed linear and exponential trends. 25 8.33 points 20 eBook 15 Hint 10 Print -Linear (y) Expon. (y) References 5 0 t 0 5 10 15 20 25 b-1. Estimate a linear trend model and an exponential trend model for the sample. (Round your answers to 2 decimal places.) Variable Linear Trend Exponential Trend Intercept t Standard Error Ch 4 Linear Trend...
(Round all intermediate calculations to at least 4 decimal places.) Consider the following sample regressions for the linear, the quadratic, and the cubic models along with their respective R2 and adj...
(Round all intermediate calculations to at least 4 decimal places.) Consider the following sample regressions for the linear, the quadratic, and the cubic models along with their respective R2 and adjusted R2. Linear Quadratic Cubic Intercept 25.97 20.73 16.20 x 0.47 2.82 6.43 x2 NA −0.20 −0.92 x3 NA NA 0.04 R2 0.060 0.138 0.163 Adjusted R2 0.035 0.091 0.093 pictureClick here for the Excel Data File a. Predict y for x = 3 and 5 with each of the...
b-2. Using the MAD method of testing the forecasting model's performance, plus actual data from 3...
b-2. Using the MAD method of testing the forecasting model's performance, plus actual data from 3 years ago through the second quarter of this year, how well did the model perform? Based on MAD, an a performs better than an a of (Click to select) c. Using the decomp (Click to select) 0.3 0.2 hod of forecasting, forecast earnings per share for the last two quarters of this year and all four quarters of next year. (Negative values should be...
The accompanying data file contains 20 observations for
t and yt.
Actual series are plotted along with the superimposed linear and
exponential trends.
t
y
t
y
t
y
t
y
1
1.91
6
4.93
11
5.96
16
15.58
2
3.57
7
6.78
12
9.02
17
12.33
3
5.83
8
4.58
13
9.52
18
13.95
4
5.39
9
7.19
14
14.02
19
15.63
5
2.78
10
8.81
15
14.57
20
19.77
The accompanying data file contains 20 observations for tand...
The accompanying data file contains 20 observations for tand yt: Click here for the Excel Data File Actual series are plotted along with the superimposed linear and exponential trends. 25 20 15 • Y 10 Linearly Expon. (v) 5 0 0 10 15 20 25 b-1. Estimate a linear trend model and an exponential trend model for the sample. (Round your answers to 2 decimal places.) Exponential Trend Variable Intercept Linear Trend 0.43 0.84 0.10 Standard Error b-2. Calculate the...
Consider the following estimated trend models. Use them to make a forecast for t=20. a. Linear Trend: ŷ = 14.32 +0.75t (Round Intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.) b. Quadratic Trend: y - 17.78 +0.94 - 0.01 2 decimal places.) (Round Intermediate calculations to at least 4 decimal places and final answer to c. Exponential Trend: In(y) - 1.9.0.076 to 2 decimal places.) -0.02 (Round Intermediate calculations to at least 4...
Consider the following estimated trend models. Use them to make a forecast for t= 24. a. Linear Trend: = 11.64 + 1.04t (Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.) Ў b. Quadratic Trend: û = 19.26 + 0.88t - 0.0172 (Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.) 9 c. Exponential Trend: In(y) = 2.4 +0.06t, se = 0.01 (Round intermediate calculations to...
Consider the following sample regressions for the linear, the quadratic, and the cubic models along with their respective R2 and adjusted R2. Intercept х x2 Linear 28.53 0.12 NA NA Quadratic 28.80 0.01 0.01 Cubic 28.62 0.15 -0.02 -0.01 x3 NA R2 Adjusted R2 0.005 -0.021 0.006 -0.048 0.006 -0.077 a. Predict y for x = 2 and 4 with each of the estimated models. (Round intermediate calculations to at least 4 decimal places and final answers to 2 decimal...
Models with quadratic terms: Using data from a random sample of 305 women, we have estimated the following model that relates a woman's sleep time in a week (in minutes) to her work time (in minutes) and age. SLEEP4206.17 -0.13 WRK- 37.64 AGE+0.47 AGE (333.60)(0.03) (17.46) (0.21) n - 305, R-0.092 (a) Explain the insights that the regression results provide for the effect of age on sleep, all else equal. In particular, all else equal, at what age women are...
Check my work 4 Click here for the Excel Data File Actual series are plotted along with the superimposed linear and exponential trends. 25 8.33 points 20 eBook 15 Hint 10 Print -Linear (y) Expon. (y) References 5 0 t 0 5 10 15 20 25 b-1. Estimate a linear trend model and an exponential trend model for the sample. (Round your answers to 2 decimal places.) Variable Linear Trend Exponential Trend Intercept t Standard Error Ch 4 Linear Trend...
b-2. Using the MAD method of testing the forecasting model's performance, plus actual data from 3 years ago through the second quarter of this year, how well did the model perform? Based on MAD, an a performs better than an a of (Click to select) c. Using the decomp (Click to select) 0.3 0.2 hod of forecasting, forecast earnings per share for the last two quarters of this year and all four quarters of next year. (Negative values should be...
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