Applying a linear regression model and fiding trends in data.

1. How these majors events reflects in the behavior of S&P500, Dow-Jones, please provide an explanation with supports and three paragraphs.

Indexes

Close of Tesla 1,400.00 1,200. 00 1,000. 00 800.00 600.00 400.00 200.00 0.00 5/10/21 6/10/21 7/10/21 8/10/21 9/10/2 10/10/21 11/10/21 12/10/21 1/10/22 2/10/22 3/10/22 4/10/22 5/10/22 Close of S&P 6,000. 00 5,000.00 4,000.00 3,000. 00 2,000. 00 1,000.00 0.00 5/10/21 6/10/21 7/10/21 8/10/21 9/10/21 10/10/21 11/10/21 12/10/21 1/10/22 2/10/2 3/10/22 4/10/22 5/10/22Close of Dow Jones 38,000.00 37,000.00 36,000.00 35,000.00 34,000.00 33,000.00 32,000.00 31,000.00 30,000.00 29,000.00 5/10/21 6/10/21 7/10/21 8/10/21 /10/2 /22 11/10/21 12/10/21 2/10/22 /10/2 10/1 1/1 4/10/22 5/10/2 Close of Tesla 1,400.00 1,200.00 1,000. 00 800.00 600.00 400.00 200.00 0.00 5/10/21 6/10/21 7/10/21 8/10/21 9/10/21 10/10/21 11/10/21 12/10/21 1/10/22 2/10/22 4/10/22 5/10/22 3/1Regression Statistics Multiple R 0.464738276 Positive Linear regression relationship R Square 0.215981665 It means 21% of regression can be explained Adjusted R 0.212870482 Standard Er 155.4443943 Observation 254 ANOVA df SS MS F ignificance F Regression 1 1677418 1677418 69.42105472 5.16E-15 Residual 252 6089066 24162.96 Total 253 7766484 Coefficients andard Erro t Stat P-value Lower 95% Upper 95% Lower 95.0% pper 95.0% Intercept -2417.704306 392.5095 -6.15961 2.86557E-09 -3190.72 -1644.687289 -3190.721322 -1644.69 Close of Do 0.09391015 0.011271 8.33193 5.16064E-15 0.071713 0.116107739 0.071712562 0.116108 Y=-2417.70430584061+0.0939101503959725X Since P