Example 10.4

EXAMPLE 10.4 Log Income and Years of Education

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CASE 10.1 Figure 10.5 displays Excel output for the regression of log income (LOGINC) on years of education (EDUC) for our sample of 100 entrepreneurs in the United States. In this output, we find the correlation and the squared correlation that we used in Example 10.2, along with the intercept and slope of the least-squares line. The regression standard error is labeled simply “Standard Error.”

Figure 10.5: FIGURE 10.5 Excel output for the regression of log average income on years of education, Example 10.4.

The three parameter estimates are

After rounding, the fitted regression line is

As usual, we ignore the parts of the output that we do not yet need. We will return to the output for additional information later.

493

Figure 10.6: FIGURE 10.6 JMP and Minitab outputs for the regression of log average income on years of education. The data are the same as in Figure 10.5.

Figure 10.6 shows the regression output from two other software packages. Although the formats differ, you should be able to find the results you need. Once you know what to look for, you can understand statistical output from almost any software.