Standard and Poor's/Toronto Stock Exchange Composite Index	Standard and Poor's/Toronto Stock Exchange 60 Index
	Index
0.00	381.23
7,092.49	406.82
7,558.50	435.32
7,664.99	440.34
7,589.78	441.02
7,366.89	427.01
6,931.43	400.51
5,530.71	318.75
5,614.12	321.55
6,208.28	359.99
6,343.87	369.21
6,485.94	375.98
6,729.56	396.87
6,312.69	368.25
6,597.79	384.98
7,014.70	410.85
6,841.80	400.07
7,010.07	411.04
7,081.03	415.1
6,970.81	407.32
6,957.72	408.54
7,256.22	433.85
7,523.23	447.29
8,413.75	495.86
8,481.11	498.59
9,128.99	519.93
9,462.39	568.89
9,347.61	559.86
9,251.99	556.35
10,195.45	617.91
10,406.31	638.35
11,247.91	687.08
10,377.92	618.28
9,639.57	569.28
8,819.92	525.33
8,933.68	528.72
9,321.87	554.84
8,078.72	472.6
7,608.00	443.04
7,946.63	459
8,161.87	471.09
7,736.35	444.84
7,689.69	445.15
7,399.22	430.33
6,838.56	398.2
6,885.70	397.55
7,425.65	431.78
7,688.41	442.55
7,648.49	438.92
7,637.50	436.48
7,851.47	446.74
7,663.39	434.04
7,656.13	429.17
7,145.61	401.2
6,605.42	371.06
6,611.95	371.8
6,180.42	345.06
6,248.79	351.36
6,570.42	372.63
6,614.54	373.15
6,569.49	370.48
6,555.12	371.97
6,343.29	361.23
6,586.07	373.94
6,859.80	388.11
6,983.14	394.63
7,257.92	409.03
7,510.32	423.28
7,421.13	416.58
7,772.70	436.2
7,859.39	438.25
8,220.89	458.72
8,521.39	476.64
8,788.49	490.59
8,585.93	475.59
8,243.97	455.87
8,417.32	463.61
8,545.58	472.78
8,458.07	469.34
8,377.03	465.48
8,668.29	482.19
8,870.97	496.37
9,030.05	501.18
9,246.65	511.91
9,204.05	506.75
9,668.32	532.08
9,612.38	533.87
9,369.30	522.02
9,607.30	536.89
9,902.77	555.06
10,422.93	585.02
10,668.94	600.4
11,011.83	620.04
10,383.32	585.55
10,824.14	611.09
11,272.26	634.72
11,945.64	672.69
11,688.34	659.27
12,110.61	682.54
12,204.17	685.33
11,744.52	657.38
11,612.87	653.46
11,830.96	667.43
12,073.75	682.21
11,761.27	673.16
12,344.59	703.41
12,752.38	732.35
12,908.39	742.77
13,034.12	747.47
13,045.02	743.77
13,165.50	752.45
13,416.68	765.35
14,056.78	804.47
13,906.57	799.7
13,868.63	799.42
13,660.48	793.37
14,098.89	817.39
14,625.00	848.82
13,689.12	798.5
13,833.06	808.53
13,155.10	772.56
13,582.69	795.23
13,350.13	783.44
13,937.04	825.91
14,714.73	878.42
14,467.03	863.19
13,592.91	811.73
13,771.25	821.69
11,752.90	707.34
9,762.76	591.28
9,270.62	563.09
8,987.70	541.82
8,694.90	523.28
8,123.02	489.56
8,720.39	528.68
9,324.83	565.38
10,370.07	632.47
10,374.91	630.06
10,787.15	654.56
10,868.21	652.78
11,394.96	680.75
10,910.75	647.72
11,447.20	680.26
11,746.11	693.23
11,094.31	648.53
11,629.63	680.76
12,037.73	706.81
12,210.70	716.05
11,762.99	691.63
11,294.42	662.05
11,713.43	685.03
11,913.86	694.05
12,368.65	715.07
12,676.24	728.09
12,952.88	741.34
13,443.22	768.65
13,551.99	778.65
14,136.50	813.29
14,116.10	810.86
13,944.79	797.9
13,802.88	789.12
13,300.87	763.9
12,945.63	733.3
12,768.70	728.2
11,623.84	667.08
12,252.06	698.04
12,204.11	695.49
11,955.09	680.87
12,452.15	709.18
12,644.01	718.86
12,392.18	706.96
12,292.69	699.79
11,513.21	656.5
11,596.56	663.62
11,664.71	665.46
11,949.26	683.47
12,317.46	702.87
12,422.91	711.58
12,239.36	702.59
12,433.53	713.72
12,685.24	727.76
12,821.83	738.55
12,749.90	731.34
12,456.50	710.71
12,650.42	726.27
12,129.11	695.52
12,486.64	714.68
12,653.90	727.13
12,787.20	732.89
13,361.26	767.47
13,395.40	771.86
13,621.55	783.75
13,694.94	785.53
14,209.59	813.25
14,335.31	820.51
14,651.87	837.58
14,604.16	836.6
15,146.01	866.04
15,330.74	884.33
15,625.73	898.26
14,960.51	864.24
14,613.32	849.5
14,744.70	863.04
14,632.44	854.85
14,673.48	857.34
15,234.34	890.4
14,902.44	869.28
15,224.52	886.56
15,014.09	875.04
14,553.33	847.78
14,468.44	853.4
13,859.12	815.45
13,306.96	784.51
13,529.17	794.49
13,469.83	791.8
13,009.95	764.54
12,822.13	754.85
12,860.35	755.27
13,494.36	790.93
13,951.45	815.46
14,065.78	821.06
14,064.54	817.65
14,582.74	847.4
14,597.95	851.38
14,725.86	858.47
14,787.27	868.38
15,082.85	888.3
15,287.59	900.05
15,385.96	909.19
15,399.24	907.57
15,547.75	915.58
15,586.13	918.9
15,349.91	906.38
15,182.19	892.65
15,143.87	891.19
15,211.87	892.56
15,634.94	921.79
16,025.59	947.17
16,067.48	952.04
16,209.13	959.69
15,951.67	944.41
15,442.68	913.9
15,367.29	908.99
15,607.88	921.43
16,061.50	950.45
16,277.73	965.32
16,434.01	979.38
16,262.88	965.73
16,073.14	952.28
15,027.28	895.08
15,197.82	913.29
14,322.86	859.32
15,540.60	929.25
15,999.01	953.91
16,102.09	959.5
16,580.73	994.53
16,037.49	961.89
16,382.20	979.6
16,406.56	979.73
16,442.07	982.45
16,658.63	997.93
16,483.16	986.33
17,040.20	1,018.62
17,063.43	1,014.92
17,318.49	1,032.97
16,263.05	972.15
13,378.75	819.89
14,780.74	891.63
15,192.83	917.17
15,515.22	934.21
16,169.20	968.67
16,514.44	990.52
16,121.38	967.27
15,580.64	928.9
17,190.25	1,023.52
17,433.36	1,034.76
17,337.02	1,026.60
18,060.26	1,073.42
18,700.67	1,117.15
19,108.33	1,138.85
19,730.99	1,180.14
20,165.58	1,209.15
20,287.80	1,216.15
20,582.94	1,231.33
20,070.25	1,203.34
21,037.07	1,265.19
20,659.99	1,248.56
21,222.84	1,286.86
21,098.29	1,281.96
21,126.36	1,278.42
21,890.16	1,322.67
20,762.00	1,255.54
20,729.34	1,254.79
18,861.36	1,146.43
19,692.92	1,187.97

Write-up a report and provide some conclusions and interpretations from your analysis in Phase 3. Question 1. Create a scatterplot for the Standard and Poor's/Toronto Stock Exchange Index time series and compute the correlation coefficient and coefficient of determination. Explain the results of these coefficients in the context of the problem. Question 2. Compute the least squares regression line and interpret the slope of the regression line in the context of this problem. Question 3. Predict the closing price of the Standard and Poor's/Toronto Stock Exchange Composite Index in July 2018 using the least-squares regression line. Compare that value to the actual value from the excel table. Are the values different? Is there a discrepancy? Explain your answer. Conduct the same prediction now for value July 2028 using the least-squares regression line. Comment on the value obtained in terms of the regression model. Question 4. Using Excel, perform exponential smoothing to the Standard and Poor's/Toronto Stock Exchange Composite Index time series using an exponential smoothing constant w = 0.8 and w = 0.2. What do you observe? Comment on the results. Question 5. From the exponential smoothing time series generated, forecast the Index value and forecast errors for July 2022 for both smoothing constants w = 0.8 and w = 0.2. Comment on your results. Question 6. Comment on the reliability of the least-squares regression and the exponential smoothing time series models, in general, in conducting predic