To estimate the salary for an employee with 19 years of experience using the given regression equation:

$\text{Estimated Salary} = 27,709.94 + 2,712.46 \times (\text{Years of Experience})$

Substitute $\text{Years of Experience} = 19$ into the equation:

$\text{Estimated Salary} = 27,709.94 + 2,712.46 \times 19$

Now, calculate the value:

$\text{Estimated Salary} = 27,709.94 + 51,554.74 = 79,264.68$

Thus, the estimated salary for an employee with 19 years of experience is $79,264.68.

Would you like more details or have any questions?

Here are some related questions to explore further:

1. How would the salary estimate change if the employee had 10 years of experience?
2. What does the coefficient $2,712.46$ represent in this regression equation?
3. How do we interpret the constant $27,709.94$ in the context of this model?
4. What is the interpretation of the regression equation as a whole?
5. How might this model be used to predict salary for employees with more than 20 years of experience?

Tip: A higher coefficient means the salary increases more per additional year of experience.