I have just finished my Big Data course for 2017, and noted some concepts that I want to teach better next year. One of them is how to interpret and use the coefficient estimates from linear regression. All economists are familiar with dense tables of coefficients and standard errors, but they require experience to read, and are not at all intuitive. Here is a more intuitive and useful way to display the same information. The blue dots show the coefficient estimates, while the lines show +/- 2 standard errors on the coefficients. It’s easy to see that the first two coefficients are “statistically significant at the 5% level”, the third one is not, and so on. More important, the figure gives a clear view

of the relative importance of different variables in determining the final outcomes.

The heavy lifting for this plot is done by the function sjp.lm from the *sjPlot* library. The main argument *linreg *is the standard results of a linear regression model, which is a complex list with all kinds of information buried in it. Continue reading