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@econometricsintro
How to read math. You’d be surprised how far this will get you.
EDIT: Some corrections
Use the Shapiro-Wilk test to test for the normality of your residuals
Cook's distance can help you to identify your outlying residuals
R-squared never decreases when you add a variable to a model.
The coefficients in a linear-log model represent the estimated unit change in your dependent variable for a percentage change in your independent variable.
http://www.dummies.com/how-to/content/the-linearlog-model-in-econometrics.html
Addressing multicollinearity
In some cases you can address a multicollinearity issue by transforming the highly correlated independent variables through a log or other transformation.
What would be a “reasonable” minimal number of observations to look for a trend over time with a linear regression? what about fitting a quadratic model?I work with composite indices of inequalit…
R² is such a lovely statistic, isn’t it? Unlike so many of the others, it makes sense–the percentage of variance in Y accounted for by a model. I mean, you can actually understand that. So can your grandmother. And the