Question

A) Forecast the demand for the next 4 periods using Exponential Constant Smoothing. Demand for 6...

A) Forecast the demand for the next 4 periods using Exponential Constant Smoothing.

Demand for 6 periods is as follows: Period 1 2 3 4 5 6

                                                                  Demand 20 22 21 18 19 28

B) Determine the bias

Homework Answers

Answer #1

Single Exponential Smoothing for demand1

Data demand1
Length 6

Smoothing Constant

? 1.77048

B] Time demand1 Smooth Predict Error
1 20 20.3159 19.5900 0.41002
2 22 23.2976 20.3159 1.68409
3 21 19.2298 23.2976 -2.29756
4 18 17.0525 19.2298 -1.22977
5 19 20.5005 17.0525 1.94751
6 28 33.7782 20.5005 7.49947

Bias = The arithematic mean of errors

Bias = sum(errors)/ n

Bias = 8.01376 /6

Bias = 1.3356

A] Forecasts

Period Forecast Lower Upper
7 33.7782 27.6254 39.9310
8 33.7782 27.6254 39.9310
9 33.7782 27.6254 39.9310
10 33.7782 27.6254 39.9310

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Using ? = 0.5 and the following data, compute exponential smoothing forecasts for periods 2 through...
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
Following are time-series data for ten different periods. Use exponential smoothing to forecast the values for...
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...
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)...
Following are time-series data for ten different periods. Use exponential smoothing to forecast the values for...
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,...
Use a simple exponential smoothing model (SES) with alpha of .4. The forecast for period 8...
Use a simple exponential smoothing model (SES) with alpha of .4. The forecast for period 8 is? period Y 1 50 2 85 3 65 4 90 5 88 6 90 7 110 8 Forecast period 8 =
The Aleidon Middle School forecasts its lunch meals using the exponential smoothing method. The recent results...
The Aleidon Middle School forecasts its lunch meals using the exponential smoothing method. The recent results and forecasts have been as follows: Forecast Actual Demand Day 1 315 325 Day 2 350 330 a) Determine the smoothing constant. (2 points) b) Provide the forecast of the lunch meals for Day 3. (2 points)
In Excel, create forecasts for periods 6-13 using each of the following methods: 5 period simple...
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. The actual values for 12 periods (shown in order) are: (1) 45  (2)...
Consider the following time series data. Week 1 2 3 4 5 6 Value 19 12...
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...
After plotting demand for four periods, an emergency room manager has concluded that a trend-adjusted exponential...
After plotting demand for four periods, an emergency room manager has concluded that a trend-adjusted exponential smoothing model is appropriate to predict future demand. The initial estimate of trend is based on the net change of 19 for the three periods from 1 to 4, for an average of +6.33 units. Period Actual Period Actual 1 202 6 251 2 221 7 266 3 216 8 276 4 221 9 281 5 241 10 Use α=.50 and β=.10, and TAF...
The actual values for 12 periods (listed in order, 1-12). In Excel, create forecasts for periods...
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...
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT