Question

Following are time-series data for ten different periods. Use exponential smoothing to forecast the values for periods 3 through 10. Use the value for the first period as the forecast for the second period. Compute forecasts using α = 0.1. Compute the MAD and MSE.

Time period | Value |

1 | 27 |

2 | 31 |

3 | 58 |

4 | 63 |

5 | 59 |

6 | 66 |

7 | 71 |

8 | 86 |

9 | 101 |

10 | 97 |

Group of answer choices

A) MAD=296.6, MSE=1266.5

B) MAD=296.6 , MSE=11398.5

C) MAD=32.9, MSE=1266.5

D) MAD=32.9, MSE=11398.5

Answer #1

for exponential smoothing: next period forecast =α*last period actual+(1-α)*last period forecast |

period | value | forecast | error | error^2 |

1 | 27 | |||

2 | 31 | 27.00 | 4.000 | 16.000 |

3 | 58 | 27.40 | 30.600 | 936.360 |

4 | 63 | 30.46 | 32.540 | 1058.852 |

5 | 59 | 33.71 | 25.286 | 639.382 |

6 | 66 | 36.24 | 29.757 | 885.503 |

7 | 71 | 39.22 | 31.782 | 1010.074 |

8 | 86 | 42.40 | 43.603 | 1901.265 |

9 | 101 | 46.76 | 54.243 | 2942.319 |

10 | 97 | 52.18 | 44.819 | 2008.728 |

11 | 56.66 | |||

average |
32.9 |
1266.5 |
||

MAE |
MSE |

**option C is correct :MAD =32.9 ; MSE
=1266.5**

Following are time-series data for ten different periods. Use
exponential smoothing to forecast the values for periods 3 through
10. Use the value for the first period as the forecast for the
second period. Compute forecasts using α = 0.8. Compute the MAD and
MSE.
Time period
Value
1
27
2
31
3
58
4
63
5
59
6
66
7
71
8
86
9
101
10
97

Following are time-series data for ten different periods. Use
exponential smoothing to forecast the values for periods 3 through
10. Use the value for the first period as the forecast for the
second period. Compute forecasts using α = 0.8. Compute the MAD and
MSE.
Time period
Value
1
27
2
31
3
58
4
63
5
59
6
66
7
71
8
86
9
101
10
97
Group of answer choices
a) MAD=9.7, MSE=1585.6
b) MAD=9.7, MSE=176.2
c) MAD=10.2,...

Consider the following time series data.
Week
1
2
3
4
5
6
Value
19
12
16
11
18
13
(b)
Develop the three-week moving average forecasts for this time
series. (Round your answers to two decimal places.)
Week
Time Series
Value
Forecast
1
19
2
12
3
16
4
11
5
18
6
13
Compute MSE. (Round your answer to two decimal places.)
MSE =
What is the forecast for week 7?
(c)
Use α = 0.2 to compute...

The actual values for 12 periods (listed in order, 1-12). In
Excel, create forecasts for periods 6-13 using each of the
following methods: 5 period simple moving average; 4 period
weighted moving average (0.63, 0.26, 0.08, 0.03); exponential
smoothing (alpha = 0.23 and the forecast for period 5 = 53); linear
regression with the equation based on all 12 periods; and quadratic
regression with the equation based on all 12
periods. Round all numerical answers to two
decimal places.
A. The...

Consider the following time series data.
Week
1
2
3
4
5
6
Value
18
13
15
12
16
14
c)Use α = 0.2 to compute the exponential smoothing
forecasts for the time series.
Week
Time Series
Value
Forecast
1
18
2
13
18
3
15
4
12
5
16
6
14
Compute MSE. (Round your answer to two decimal places.)
MSE =____
What is the forecast for week 7? (Round your answer to two
decimal places.)
____
(e)Use a...

(b)
Develop the three-week moving average forecasts for this time
series. (Round your answers to two decimal places.)
Week
Time Series
Value
Forecast
1
16
2
11
3
13
4
10
5
14
6
12
Compute MSE. (Round your answer to two decimal places.)
MSE =
What is the forecast for week 7?
(c)
Use α = 0.2 to compute the exponential smoothing
forecasts for the time series.
Week
Time Series
Value
Forecast
1
16
2
11
3
13
4...

Instructions
The Data contains the actual values for 12 periods (listed in
order, 1-12). In Excel, create forecasts for periods 6-13 using
each of the following methods: 5 period simple moving average; 4
period weighted moving average (0.63, 0.26, 0.08, 0.03);
exponential smoothing (alpha = 0.23 and the forecast for period 5 =
53); linear regression with the equation based on all 12 periods;
and quadratic regression with the equation based on all 12
periods. Round all numerical answers to two...

Question 1 contains the actual values for 12 periods (listed in
order, 1-12). In Excel, create forecasts for periods 6-13 using
each of the following methods: 5 period simple moving average; 4
period weighted moving average (0.63, 0.26, 0.08, 0.03);
exponential smoothing (alpha = 0.23 and the forecast for period 5 =
53); linear regression with the equation based on all 12 periods;
and quadratic regression with the equation based on all 12 periods.
Round all numerical answers to two...

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Month
1
2
3
4
5
6
7
Value
22
11
18
10
17
21
13
A) What type of pattern exists in the data?
The data appear to follow a seasonal pattern.
The data appear to follow a trend
pattern.
The data appear to follow a horizontal pattern.
The data appear to follow a cyclical pattern.
B) Develop the three-month moving average forecasts for this
time series.
Month
Time Series
Value
Forecast
1...

Using ? = 0.5 and the following data, compute exponential
smoothing forecasts for periods 2 through 8. (Round your
intermediate calculations and final answers to 2 decimal places.)
Period: 1 2 3 4 5 6 7 Forecast: 10 Actual demand: 12 15 11 13 11 11
10

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