Question

A. Use a 3-year moving average to forecast the quantity of fish for the years 1983 through 2006 for these data. Compute the error of each forecast and then determine the mean absolute deviation of error for the forecast. B. Use exponential smoothing and a = 0.2 to forecast the data through 2006. Let the forecast for 1981 equal the actual value for 1980. Compute the error of each forecast and then determine the mean absolute deviation of error for the forecast. C. Use the data to develop a simple regression forecasting model that attempts to predict the quantity (million pounds) of U.S. domestic fish by year D. Compute a Durbin-Watson statistic for this regression model and determine whether significant autocorrelation is present. Let a=0.05. Year Quantity 1980 1981 6482 5977 1982 1983 6367 6439 1984 6438 1985 6258 1986 6031 6896 1987 1988 7192 8463 1989 1990 9404 1991 9484 1992 9637 1993 1994 10467 61 1995 9788 1996 9565 1997 1998 9842 9194 9339 1999 2000 9069 2001 2002 9489 9397 2003 9507 2004 9683 2005 9707 What is the forecast quantity of U.S. domestic fish caught in 2013? 11,657 10,001 303,997 315,653 Using a 0.05 the critical value of the Durbin-Watson statistic, dL, is 1.09 1.23 1.32 1.47 Using a 3-year moving average, the forecast value for the year 2003 would be 9318.33 9299 6229.5 9464.33 The Durbin-Watson Statistic for this simple regression forecasting model is 0.387 0.515 0.235 0.125 2 0.253 Question 5 (2 points) Based on the Durbin-Watson Statistic for this simple regression forecasting model, what relation would you expect among the residuals/errors? Negative Autocorrelation Positive Autocorrelation Homoscedasticity Linear Regression

Answer 1

Ans A:

Year	Quantity	3-year moving average	Error	Abs error
1980	6482
1981	5977
1982	6367
1983	6439	6275	164	164		MAD	539.5797
1984	6438	6261	177	177
1985	6258	6415	-157	157
1986	6031	6378	-347	347
1987	6896	6242	654	654
1988	7192	6395	797	797
1989	8463	6706	1757	1757
1990	9404	7517	1887	1887
1991	9484	8353	1131	1131
1992	9637	9117	520	520
1993	10467	9508	959	959
1994	10461	9863	598	598
1995	9788	10188	-400	400
1996	9565	10239	-674	674
1997	9842	9938	-96	96
1998	9194	9732	-538	538
1999	9339	9534	-195	195
2000	9069	9458	-389	389
2001	9489	9201	288	288
2002	9397	9299	98	98
2003	9507	9318	189	189
2004	9683	9464	219	219
2005	9707	9529	178	178
2006		9632

Ans B:

Year	Quantity	3-year moving average	Error	Abs Error
1980	6482
1981	5977	6482	-505	505
1982	6367	6381	-14	14
1983	6439	6378	61	61
1984	6438	6390	48	48		MAD	716.9059
1985	6258	6400	-142	142
1986	6031	6372	-341	341
1987	6896	6303	593	593
1988	7192	6422	770	770
1989	8463	6576	1887	1887
1990	9404	6953	2451	2451
1991	9484	7443	2041	2041
1992	9637	7852	1785	1785
1993	10467	8209	2258	2258
1994	10461	8660	1801	1801
1995	9788	9020	768	768
1996	9565	9174	391	391
1997	9842	9252	590	590
1998	9194	9370	-176	176
1999	9339	9335	4	4
2000	9069	9336	-267	267
2001	9489	9282	207	207
2002	9397	9324	73	73
2003	9507	9338	169	169
2004	9683	9372	311	311
2005	9707	9434	273	273
2006		9489

Ans C:

Year	Quantity	Forecast
1980	6482	6403
1981	5977	6570
1982	6367	6737
1983	6439	6903
1984	6438	7070
1985	6258	7237
1986	6031	7403
1987	6896	7570
1988	7192	7737
1989	8463	7903
1990	9404	8070
1991	9484	8237
1992	9637	8403
1993	10467	8570
1994	10461	8737
1995	9788	8904
1996	9565	9070
1997	9842	9237
1998	9194	9404
1999	9339	9570
2000	9069	9737
2001	9489	9904
2002	9397	10070
2003	9507	10237
2004	9683	10404
2005	9707	10570
2006		10737
2007		10904
2008		11071
2009		11237
2010		11404
2011		11571
2012		11737
2013		11904

Quantity 12000 y 166.69x- 323643 10000 8000 6000 4000 2000 0 1975 1980 1985 1990 1995 2000 2005 2010