Based solely on the information in this output, which of the following is the best answer? (5) The data set contains no trend or seasonality. The data set contains trend but no seasonality. The data set contains seasonality but no trend. The data set pro

I need an explanation for this Economics question to help me study.

  1. The table below features three forecasting models used on the same set of data.

Model 1

Model 2

Model 3

Type

Exponential Smoothing

Regression

Seasonal & Trend

MSE

8755.3

4876.2

5945.8

Based solely on the information in this output, which of the following is the best answer?(5)

  1. The data set contains no trend or seasonality.
  2. The data set contains trend but no seasonality.
  3. The data set contains seasonality but no trend.
  4. The data set probably contains cyclicality.
  5. The data set contains both trend and seasonality.
  1. In a forecasting application for 20 time periods, there are 10 negative errors and 10 positive errors.This indicates the model is performing well.(2)
  1. True
  2. False
  1. Refer to the following graph:

Which of the following apply?(8)

  1. The data contain a trend component.
  2. The data contain a seasonal component.
  3. The data ,contain a cyclical component.
  4. The data contain an irregular (random) component.
  1. In #3, which method (if any) is most appropriate?(4)
  1. Exponential smoothing.
  2. Regression.
  3. Regression with seasonal indices.
  4. None of the above.
  1. In #3, which of the following is most appropriate regarding sales?(4)
  1. We should use all of the data in our model.
  2. We should use only periods 5-16 in our model.
  3. We should use only periods 9-16 in our model.
  4. We should use only periods 13-16 in our model.
  5. We should use only periods 1-12 in our model.
  1. Refer to the Excel output on the final pages.Here, we are tracking the number of orders placed by week for a 20-week period.The first set of output is for an exponential smoothing model with α = 0.25.The second set of output is for a regression.Which of the following is most appropriate?(3)
  1. The exponential smoothing model is most appropriate.
  2. The regression is most appropriate.
  3. Another model would be more appropriate.
  1. The model with the lower MSE is always the most appropriate model.(2)
  1. True
  2. False
  1. In a given application, we are using regression with seasonal indices.The regression model is y = 42 + 2.5t.The seasonal indices for quarters 1-4 are 0.85, 0.92, 0.98, and 1.25, respectively.The predicted value for period 20 is ___________.(5)
  1. If our data contains seasonality but no trend, exponential smoothing is appropriate.(2)
  1. True
  2. False
  1. Annual data can exhibit seasonality.(2)
  1. True
  2. False
  1. We can assess quarterly seasonality with one year of data.(2)
  1. True
  2. False

Week

Orders

Forecast

Error

Error^2

1

45

#N/A

#N/A

2

56

45

11

121

3

65

47.75

17.25

297.5625

4

63

52.0625

10.9375

119.6289

5

54

54.79688

-0.79688

0.63501

6

60

54.59766

5.402344

29.18532

7

54

55.94824

-1.94824

3.795648

8

60

55.46118

4.538818

20.60087

9

56

56.59589

-0.59589

0.35508

10

57

56.44691

0.553085

0.305903

11

50

56.58519

-6.58519

43.36467

12

61

54.93889

6.06111

36.73706

13

47

56.45417

-9.45417

89.38128

14

56

54.09063

1.909375

3.645712

15

55

54.56797

0.432031

0.186651

16

52

54.67598

-2.67598

7.160852

17

57

54.00698

2.993017

8.958153

18

58

54.75524

3.244763

10.52849

19

61

55.56643

5.433572

29.52371

20

47

56.92482

-9.92482

98.50207

MSE =

48.47673

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.139263

R Square

0.019394

Adjusted R Square

-0.03508

Standard Error

5.524367

Observations

20

ANOVA

df

SS

MS

F

Significance F

Regression

1

10.86466

10.86466

0.356001

0.558166112

Residual

18

549.3353

30.51863

Total

19

560.2

Coefficients

Standard Error

t Stat

P-value

Intercept

57.04211

2.566242

22.22787

1.54E-14

Week

-0.12782

0.214226

-0.59666

0.558166

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