6. DATABASES AND DATA MANAGEMENT (Contd.)

Table 6.10.3 Example of tables with data of FDDB.

INTERVIEWS

ID_IntvieW	ID_Province	ID_Vessel	Effort	Date of Sampling
2	XXX	X_A_01	9	04-Sep-97
3	XXX	X_A_02	9	05-Sep-97
4	XXX	X_A_03	8	06-Sep-97
5	XXX	X_B_01	5	07-Sep-97
6	XXX	X_B_02	8	08-Sep-97
7	XXX	X_B_03	6	09-Sep-97
8	XXX	X_C_01	9	10-Sep-97
9	XXX	X_C_02	9	11-Sep-97
10	YYY	Y_A_01	4	12-Sep-97
11	YYY	Y_A_02	6	13-Sep-97
12	YYY	Y_A_03	7	14-Sep-97
13	YYY	Y_B_01	8	15-Sep-97
14	YYY	Y_B_02	6	16-Sep-97
15	YYY	Y_B_03	3	17-Sep-97
16	YYY	Y_C_01	4	18-Sep-97
17	YYY	Y_C_02	8	19-Sep-97
18	ZZZ	Z_A_01	6	20-Sep-97
19	ZZZ	Z_A_02	5	21-Sep-97
20	ZZZ	Z_A_03	8	22-Sep-97
21	ZZZ	Z_B_01	9	23-Sep-97
22	ZZZ	Z_B_02	6	24-Sep-97
23	ZZZ	Z_B_03	6	25-Sep-97
24	ZZZ	Z_C_01	6	26-Sep-97
25	ZZZ	Z_C_02	7	27-Sep-97
26	ZZZ	Z_C_02	12	05-Sep-97
27	ZZZ	Z_B_03	12	04-Sep-97

EXERCISE

The exercise is to raise the samples to total country, (or division of country) as explained in the manual. The raising is for all three types of data:

Catch by commercial category
Catch by species.
Length frequencies.

What you should do is take the tables from FDDB, and send them to EXCEL (the spread sheet module of Microsoft Office), and then do the raising in EXCEL. This could also be done in ACCESS, but that is a job for experts.

One of the problems you will have to deal with is "how to calculate mean values of CPUE (Catch Per Unit of Effort)?

Effort	= Fishing days
CPUE	= Catch per days

We want to calculate the mean CPUE for a fleet (similar boats). We observe the number of days per trip and the total catch of the trip. Which method to use, A or B?

Method A	Effort	Catch	CPUE
Vessel 1	1	100	100.00
Vessel 2	5	200	40.00
Vessel 3	10	500	50.00
	*Mean CPUE*		63.33

Method B	Effort	Catch	Mean
Vessel 1	1	100	*CPUE*
Vessel 2	5	200
Vessel 3	10	500
Total	16	800	50.00

If the number of fishing days per trip remains constant, the two methods give the same results.

Method A	Effort	Catch	CPUE
Vessel 1	5	150	30.00
Vessel 2	5	200	40.00
Vessel 3	5	250	50.00
	*Mean CPUE*		40.00

Method B	Effort	Catch	Mean
Vessel 1	5	150	*CPUE*
Vessel 2	5	200
Vessel 3	5	250
Total	15	600	40.00

Table 6.10.4 Example of tables with data of FDDB.

ID_ComGr_Wgt	ID_IntvieW	ID_Comm Group	Weight CommGr	SpecComp Samp	Sample Weight
2	2	CG_X_A_01	142	TRUE	18.9
3	2	CG_X_A_02	188	FALSE	0
4	2	CG_X_A_03	108	FALSE	0
5	3	CG_X_A_01	180	TRUE	12.8
6	3	CG_X_A_02	106	FALSE	0
7	3	CG_X_A_03	166	FALSE	0
8	4	CG_X_A_01	135	FALSE	0
9	4	CG_X_A_02	110	FALSE	0
10	4	CG_X_A_03	139	TRUE	15.2
11	5	CG_X_B_01	121	TRUE	14.2
12	5	CG_X_B_02	132	TRUE	16.8
13	6	CG_X_B_01	183	FALSE	0
14	6	CG_X_B_02	139	FALSE	0
15	7	CG_X_B_01	188	FALSE	0
16	7	CG_X_B_02	122	TRUE	10.1
17	8	CG_X_C_01	127	TRUE	15.2
18	8	CG_X_C_02	191	FALSE	0
19	9	CG_X_C_01	111	FALSE	0
20	9	CG_X_C_02	134	FALSE	0
21	10	CG_Y_A_01	142	FALSE	0
22	10	CG_Y_A_02	161	FALSE	0
23	10	CG_Y_A_03	129	FALSE	0
24	11	CG_Y_A_01	104	FALSE	0
25	11	CG_Y_A_02	150	TRUE	16
26	11	CG_Y_A_03	135	FALSE	0
27	12	CG_Y_A_01	132	TRUE	16.8
28	12	CG_Y_A_02	190	FALSE	0
29	12	CG_Y_A_03	107	TRUE	12.6
30	13	CG_Y_B_01	174	FALSE	0
31	13	CG_Y_B_02	144	FALSE	0
32	14	CG_Y_B_01	107	FALSE	0
33	14	CG_Y_B_02	122	TRUE	10.1
34	15	CG_Y_B_01	156	FALSE	0
35	15	CG_Y_B_02	102	TRUE	10.8
36	16	CG_Y_C_01	108	FALSE	0
37	16	CG_Y_C_02	147	FALSE	0
38	17	CG_Y_C_01	108	FALSE	0
39	17	CG_Y_C_02	114	FALSE	0
40	18	CG_Z_A_01	150	FALSE	0
41	18	CG_Z_A_02	142	TRUE	16.8
42	18	CG_Z_A_03	145	FALSE	0
43	19	CG_Z_A_01	175	FALSE	0
44	19	CG_Z_A_02	169	FALSE	0
45	19	CG_Z_A_03	158	FALSE	0
46	20	CG_Z_A_01	163	FALSE	0
47	20	CG_Z_A_02	128	FALSE	0
48	20	CG_Z_A_03	159	FALSE	0
49	21	CG_Z_B_01	162	TRUE	16.6
50	21	CG_Z_B_02	129	FALSE	0
51	22	CG_Z_B_01	102	TRUE	7.2
52	22	CG_Z_B_02	174	TRUE	9.3
53	23	CG_Z_B_01	143	FALSE	0
54	23	CG_Z_B_02	179	FALSE	0
55	24	CG_Z_C_01	125	FALSE	0
56	24	CG_Z_C_02	128	FALSE	0
57	25	CG_Z_C_01	131	TRUE	14.2
58	25	CG_Z_C_02	133	TRUE	14
59	26	CG_X_A_02	120	FALSE	0
60	27	CG_Z_B_01	130	TRUE	25