in roughly 500 words, summarize the patterns in the data and assess how the patterns you observe in 2020 differ from what we saw in 2016. Did Biden outperform Clinton? Did Trump outperform or under perform his 2016 showing? Why did we ultimately see a different result? Use examples from the data to bolster your claims

Linear regression-Biden's 2020 vote share as a function of Clinton's 2016 vote share

Biden_Pct	Coef.	St.Err.	t-value	p-value	[95% Conf	Interval]	Sig
ClintonPct	.975	.024	41.06	0	.927	1.023	***
Constant	5.115	1.097	4.66	0	2.909	7.32	***
Mean dependent var	48.608	SD dependent var	12.054
R-squared	0.972	Number of obs	51
F-test	1685.748	Prob > F	0.000
Akaike crit. (AIC)	219.736	Bayesian crit. (BIC)	223.600
*** p<.01, ** p<.05, * p<.1

Linear regression-Trump's 2020 vote share as a function of Trump's 2016 vote share

Trump_Vote_201	1.486	.111	13.38	0	1.263	1.709	***
Constant	-241853.27	186030.56	-1.30	.2	-615695.68	131989.14
Mean dependent var	1593627.745	SD dependent var	1916161.970
R-squared	0.785	Number of obs	51
F-test	179.011	Prob > F	0.000
Akaike crit. (AIC)	1544.821	Bayesian crit. (BIC)	1548.684
*** p<.01, ** p<.05, * p<.1

Linear regression-other candidate vote share in 2020 as a function of other candidate vote share in 2016

Other_2020	Coef.	St.Err.	t-value	p-value	[95% Conf	Interval]	Sig
Other_2016	33.903	.989	34.28	0	31.916	35.89	***
Constant	78592.046	227758.26	0.35	.732	-379105.3	536289.4
Mean dependent var	5599072.549	SD dependent var	5692675.118
R-squared	0.960	Number of obs	51
F-test	1175.457	Prob > F	0.000
Akaike crit. (AIC)	1570.160	Bayesian crit. (BIC)	1574.024
*** p<.01, ** p<.05, * p<.1