In: Statistics and Probability
DistCo, a large warehouse service company in the San Francisco Bay Area, stores pharmaceutical products for customers while they are in transit to local retailers. DistCo can store a maximum of 280,000 cases of products at its present facility. Because their business has been growing, the company's management wonders if they should acquire other warehouses in 2001.
The materials specialist has accumulated the following inventory data: Inventory (thousand Year Quarter Period of cases)
Inventory (thousand
Year Quarter Period of cases)
______________________________________
1996 1 1 176
2 2 134
3 3 186
4 4 195
1997 1 5 189
2 6 157
3 7 195
4 8 211
1998 1 9 205
2 10 180
3 11 212
4 12 229
1999 1 13 223
2 14 192
3 15 234
4 16 248
2000 1 17 239
2 18 217
3 19 271
4 20 284
(a) Briefly introduce each time-series method (e.g., moving average, exponential smoothing, linear trend, trend with seasonal factors) used in your forecasting.
(b) Explain how you select the best time-series forecasting model and why it is better than the others are. What is the forecast performance? What quarterly inventory is to be expected in each quarter of 2001?
Hint: You may include the following elements in your answer
· Explain how to measure forecast accuracy using MSE:
o The MSE (mean squared error) is a measure of the quality of an estimator—it is always non-negative, and values closer to zero are better. In statistics, the mean squared error (MSE) measures the average of the squares of the errors—that is, the average squared difference between the estimated values and what is estimated.
· Compare MSE of different methods.
· Explain which method is best and why (by observing patterns in actual data).
· Conclude with your forecast results in 2001
(c) Should DistCo acquire more warehouse capacity in 2001? Please explain and justify your opinion.
(d) What are the potential factors that may affect the forecast accuracy of the model you have selected?
Hint: There are always some factors not be able to consider in time-series analysis. For example, interest rate, GDP, political event, natural event, etc.
SOLUTION:-
[a] Detailed process of calculation of regression equation and MSE is as follows
Regression equation: y = 154.353+5.19x
MSE =358
MSE = 358
[b] Quadratic model: y = 165.566 + 2.127x + 0.146x2
MSE = 339
Please give thumb up...
Thank you in advance....