Step 1: Statistical Significance

This section shows how to identify statistically significant coefficients, and a basic idea of how to interpret that statistical significance.

The coefficient/slope for county income, $-0.158$, is starred. This indicates that it is a statistically significant coefficient.
The star indicates that we believe that the direction of the best fit line/the sign of the coefficient is not zero with at least 95% confidence.
The confidence threshold here is 95% because $p<0.05$. If the p-value were set to 0.01, we would be working with a 99% confidence threshold. If $p<0.001$, then the confidence threshold would be 99.9%.

Additional notes:

Not all regression tables use stars to indicate statistical significance. You can roughly calculate whether the coefficient/slope will be starred by using the number in parentheses below the coefficient. This is the standard error, a measure of confidence in the coefficient. If $2*(\text{standard error}) < |\text{coefficient}|$, then there is likely to be a star on the coefficient.
As shown below, this inequality is true in this case, so there is a star on $-0.158$.

\[\begin{align} 2*(\text{standard error}) &< |\text{coefficient}| \\ 2*(0.006) &< |-0.158|\\ 0.012 &< 0.158\\ \end{align}\]

In general, the coefficient for the constant term is ignored regardless of its statistical significance.