Use the data from the following file (Fish.csv) table pasted below for running linear regression.

Weight	Length1	Length2	Length3	Height	Width
242	23.2	25.4	30	11.52	4.02
290	24	26.3	31.2	12.48	4.3056
340	23.9	26.5	31.1	12.3778	4.6961
363	26.3	29	33.5	12.73	4.4555
430	26.5	29	34	12.444	5.134
450	26.8	29.7	34.7	13.6024	4.9274
500	26.8	29.7	34.5	14.1795	5.2785
390	27.6	30	35	12.67	4.69
450	27.6	30	35.1	14.0049	4.8438
500	28.5	30.7	36.2	14.2266	4.9594
475	28.4	31	36.2	14.2628	5.1042
500	28.7	31	36.2	14.3714	4.8146
500	29.1	31.5	36.4	13.7592	4.368
340	29.5	32	37.3	13.9129	5.0728
600	29.4	32	37.2	14.9544	5.1708
600	29.4	32	37.2	15.438	5.58
700	30.4	33	38.3	14.8604	5.2854
700	30.4	33	38.5	14.938	5.1975
610	30.9	33.5	38.6	15.633	5.1338
650	31	33.5	38.7	14.4738	5.7276
575	31.3	34	39.5	15.1285	5.5695
685	31.4	34	39.2	15.9936	5.3704
620	31.5	34.5	39.7	15.5227	5.2801
680	31.8	35	40.6	15.4686	6.1306
700	31.9	35	40.5	16.2405	5.589
725	31.8	35	40.9	16.36	6.0532
720	32	35	40.6	16.3618	6.09
714	32.7	36	41.5	16.517	5.8515
850	32.8	36	41.6	16.8896	6.1984
1000	33.5	37	42.6	18.957	6.603
920	35	38.5	44.1	18.0369	6.3063
955	35	38.5	44	18.084	6.292
925	36.2	39.5	45.3	18.7542	6.7497
975	37.4	41	45.9	18.6354	6.7473
950	38	41	46.5	17.6235	6.3705
40	12.9	14.1	16.2	4.1472	2.268
69	16.5	18.2	20.3	5.2983	2.8217
78	17.5	18.8	21.2	5.5756	2.9044
87	18.2	19.8	22.2	5.6166	3.1746
120	18.6	20	22.2	6.216	3.5742
0	19	20.5	22.8	6.4752	3.3516
110	19.1	20.8	23.1	6.1677	3.3957
120	19.4	21	23.7	6.1146	3.2943
150	20.4	22	24.7	5.8045	3.7544
145	20.5	22	24.3	6.6339	3.5478
160	20.5	22.5	25.3	7.0334	3.8203
140	21	22.5	25	6.55	3.325
160	21.1	22.5	25	6.4	3.8
169	22	24	27.2	7.5344	3.8352
161	22	23.4	26.7	6.9153	3.6312
200	22.1	23.5	26.8	7.3968	4.1272
180	23.6	25.2	27.9	7.0866	3.906
290	24	26	29.2	8.8768	4.4968
272	25	27	30.6	8.568	4.7736
390	29.5	31.7	35	9.485	5.355
270	23.6	26	28.7	8.3804	4.2476
270	24.1	26.5	29.3	8.1454	4.2485
306	25.6	28	30.8	8.778	4.6816
540	28.5	31	34	10.744	6.562
800	33.7	36.4	39.6	11.7612	6.5736
1000	37.3	40	43.5	12.354	6.525
55	13.5	14.7	16.5	6.8475	2.3265
60	14.3	15.5	17.4	6.5772	2.3142
90	16.3	17.7	19.8	7.4052	2.673
120	17.5	19	21.3	8.3922	2.9181
150	18.4	20	22.4	8.8928	3.2928
140	19	20.7	23.2	8.5376	3.2944
170	19	20.7	23.2	9.396	3.4104
145	19.8	21.5	24.1	9.7364	3.1571
200	21.2	23	25.8	10.3458	3.6636
273	23	25	28	11.088	4.144
300	24	26	29	11.368	4.234
5.9	7.5	8.4	8.8	2.112	1.408
32	12.5	13.7	14.7	3.528	1.9992
40	13.8	15	16	3.824	2.432
51.5	15	16.2	17.2	4.5924	2.6316
70	15.7	17.4	18.5	4.588	2.9415
100	16.2	18	19.2	5.2224	3.3216
78	16.8	18.7	19.4	5.1992	3.1234
80	17.2	19	20.2	5.6358	3.0502
85	17.8	19.6	20.8	5.1376	3.0368
85	18.2	20	21	5.082	2.772
110	19	21	22.5	5.6925	3.555
115	19	21	22.5	5.9175	3.3075
125	19	21	22.5	5.6925	3.6675
130	19.3	21.3	22.8	6.384	3.534
120	20	22	23.5	6.11	3.4075
120	20	22	23.5	5.64	3.525
130	20	22	23.5	6.11	3.525
135	20	22	23.5	5.875	3.525
110	20	22	23.5	5.5225	3.995
130	20.5	22.5	24	5.856	3.624
150	20.5	22.5	24	6.792	3.624
145	20.7	22.7	24.2	5.9532	3.63
150	21	23	24.5	5.2185	3.626
170	21.5	23.5	25	6.275	3.725
225	22	24	25.5	7.293	3.723
145	22	24	25.5	6.375	3.825
188	22.6	24.6	26.2	6.7334	4.1658
180	23	25	26.5	6.4395	3.6835
197	23.5	25.6	27	6.561	4.239
218	25	26.5	28	7.168	4.144
300	25.2	27.3	28.7	8.323	5.1373
260	25.4	27.5	28.9	7.1672	4.335
265	25.4	27.5	28.9	7.0516	4.335
250	25.4	27.5	28.9	7.2828	4.5662
250	25.9	28	29.4	7.8204	4.2042
300	26.9	28.7	30.1	7.5852	4.6354
320	27.8	30	31.6	7.6156	4.7716
514	30.5	32.8	34	10.03	6.018
556	32	34.5	36.5	10.2565	6.3875
840	32.5	35	37.3	11.4884	7.7957
685	34	36.5	39	10.881	6.864
700	34	36	38.3	10.6091	6.7408
700	34.5	37	39.4	10.835	6.2646
690	34.6	37	39.3	10.5717	6.3666
900	36.5	39	41.4	11.1366	7.4934
650	36.5	39	41.4	11.1366	6.003
820	36.6	39	41.3	12.4313	7.3514
850	36.9	40	42.3	11.9286	7.1064
900	37	40	42.5	11.73	7.225
1015	37	40	42.4	12.3808	7.4624
820	37.1	40	42.5	11.135	6.63
1100	39	42	44.6	12.8002	6.8684
1000	39.8	43	45.2	11.9328	7.2772
1100	40.1	43	45.5	12.5125	7.4165
1000	40.2	43.5	46	12.604	8.142
1000	41.1	44	46.6	12.4888	7.5958
200	30	32.3	34.8	5.568	3.3756
300	31.7	34	37.8	5.7078	4.158
300	32.7	35	38.8	5.9364	4.3844
300	34.8	37.3	39.8	6.2884	4.0198
430	35.5	38	40.5	7.29	4.5765
345	36	38.5	41	6.396	3.977
456	40	42.5	45.5	7.28	4.3225
510	40	42.5	45.5	6.825	4.459
540	40.1	43	45.8	7.786	5.1296
500	42	45	48	6.96	4.896
567	43.2	46	48.7	7.792	4.87
770	44.8	48	51.2	7.68	5.376
950	48.3	51.7	55.1	8.9262	6.1712
1250	52	56	59.7	10.6863	6.9849
1600	56	60	64	9.6	6.144
1550	56	60	64	9.6	6.144
1650	59	63.4	68	10.812	7.48
6.7	9.3	9.8	10.8	1.7388	1.0476
7.5	10	10.5	11.6	1.972	1.16
7	10.1	10.6	11.6	1.7284	1.1484
	10.4	11	12	2.196	1.38
	10.7	11.2	12.4	2.0832	1.2772
	10.8	11.3	12.6	1.9782	1.2852
	11.3	11.8	13.1	2.2139	1.2838
	11.3	11.8	13.1	2.2139	1.1659
	11.4	12	13.2	2.2044	1.1484
	11.5	12.2	13.4	2.0904	1.3936
	11.7	12.4	13.5	2.43	1.269
	12.1	13	13.8	2.277	1.2558
	13.2	14.3	15.2	2.8728	2.0672
	13.8	15	16.2	2.9322	1.8792

Consider the Weight of the fish to be the dependent variable, and rest of the variables as independent variables.

After running the regression in Excel, define the output in words.

Also, predict the value of weight for row numbers 150 to 160.