OLS Regression Results

Dep. Variable:	temperature_norm	R-squared:	0.778
Model:	OLS	Adj. R-squared:	0.777
Method:	Least Squares	F-statistic:	693.6
Date:	Sun, 09 Feb 2025	Prob (F-statistic):	1.29e-66
Time:	12:29:12	Log-Likelihood:	-133.31
No. Observations:	200	AIC:	270.6
Df Residuals:	198	BIC:	277.2
Df Model:	1
Covariance Type:	nonrobust

	coef	std err	t	P>|t|	[0.025	0.975]
const	-1.271e-16	0.033	-3.79e-15	1.000	-0.066	0.066
latitude_norm	-0.8820	0.033	-26.336	0.000	-0.948	-0.816

Omnibus:	19.398	Durbin-Watson:	1.440
Prob(Omnibus):	0.000	Jarque-Bera (JB):	11.222
Skew:	0.423	Prob(JB):	0.00366
Kurtosis:	2.205	Cond. No.	1.00

Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.