$\ln{(\text{hourly earnings})_i} = \alpha + \beta \cdot (\text{years of schooling})_i + \varepsilon_i$
From the table, the education coefficient is 0.100, with a (0.001) underneath it. This means that our $$\beta$$ value is equal to 0.100. What does the (0.001) mean? It is the standard error, which is essentially a measure of our uncertainty. From Data 8, the standard error is most similar to the standard deviation of sample means, which is a measure of the spread in the population mean. Similarly, the the standard error here is a measure of the spread in the population coefficient. We can use the standard error to construct a confidence interval of the actual coefficient: a 95% confidence interval is between 2 standard errors above and below the reported value.