1. Run a simple linear regression using EXCEL (11 Marks)
   1. Use Time periodand Stock 1 pricesShow the output from Excel ( note the weeks must be changed to time periods 1,2,3...)
   2. Set up the linear regression equation Stock 2
   3. Test the significance using p-value with =0.05. Stock 2
   4. Use Linear regression equation (from b) forecast the stock price for end of May 2022. Stock 2
   5. Draw Time-series plot for Stock 2
   6. Do you notice any trend in e)? How would you adjust your forecast above in d)?

Stock 1 prices
weekly rate of return	DEVIDATION OF STANDARD RATE OF RETURN
239.48
232.79	-2.793552698
219.62	-5.657459513
219.91	0.132046262
237.72	8.098767678
265.93	11.86690224
270.85	1.850110931
227.11	-16.14916005
218.41	-3.830742812
241.72	10.67258825
224.3	-7.206685421
208.47	-7.05751226
229.51	10.09257927
258.37	12.57461549
263.08	1.822967063
245.11	-6.830621864
247.76	1.08114724
223.96	-9.606070391
197.13	-11.97981782
204.91	3.946634201
220.9	7.803425894
211.43	-4.287007696
217.14	2.700657428
236.13	8.745509809
244.15	3.396434168
241.85	-0.942043826
235.9	-2.460202605
235.16	-0.313692242
260.59	10.81391393
255.28	-2.037683718
281.81	10.39251018
268.59	-4.691103935
257.35	-4.184817007
262.13	1.857392656
265.94	1.453477282
251.54	-5.414755208
255.09	1.411306353
266.72	4.559175193
239.84	-10.0779844
249.16	3.885923949
247.41	-0.702359929
265.08	7.141991027
261.33	-1.41466727
247.46	-5.307465656
226.51	-8.466014709
230.35	1.695289391
215.65	-6.381593228
192.15	-10.89728727
186.75	-2.81030445
165.88	-11.17536814
167.71	1.103207138
165.34	-1.413153658
144.66	-12.50756018
136.95	-5.329738698
127.58	-6.841913107
105.64	-17.19705283
101.5	-3.918970087
108.94	7.330049261
104.02	-4.516247476
94.99	-8.68102288
119.82	26.13959364