**ECON 230**

**All of the practice
problems can be found here:**

**The solutions to all
the practice problems can be found here:**

**Assignments:**

Chapter 1: Problems 1.32, 1.33, 1.34, 1.35, 1.38, 1.40

Chapter 2: Problems 2.70, 2.72, 2.76, 2.78, 2.86, 2.87, 2.92

Chapter 3: Problems 3.112, 3.116, 3.119 (parts a and c only), 3.125, 3.128, 3.135, 3.138

Chapter 4: Problems 4.125, 4.128, 4.131, 4.136, 4.138, 4.141, 4.146

Chapter 5: Problems 5.2, 5.9, 5.17, 5.21, 5.36, 5.38, 5.88, 5.96

Chapter 6: Problems 6.11, 6.30, 6.36, 6.43, 6.49, 6.52, 6.61

Chapter 7: Problems 7.12, 7.17, 7.23, 7.45, 7.54, 7.81

Chapter 8: Problems 8.16, 8.25. 8.35, 8.49, 8.56

Chapter 9: Problems 9.1, 9.5, 9.9, 9.28, 9.30, 9.42, 9.48, 9.60, 9.85

Chapter 11: Problem 11.13, 11.19, 11.37, 11.56

Chapter 13: The problems on the following page

Chapter 13 problems:

Suppose we run a regression of an LMU
alumnus’s salary on his/her GPA for a group of 36 alumni, so the *y* variable is salary and the *x* variable is GPA. The graph below plots all the data for your
36 individuals.

Suppose that the slope of the regression line is $11,300 and that the intercept is $15,800.

1) Draw a reasonable regression line for this data.

2) The
estimated equation for the regression line is *y* = $15,800 + $11,300*x* + *u*, where *u* is the random error term. Suppose that you meet an alumnus named
Henry, who tells you his GPA at LMU was 1.0. Based on the equation above, what
is our estimate of Henry’s salary based on his GPA?

3) If the standard error of the estimate of the slope is $1500, can we conclude that GPA affects salary at the 1% significance level?