TEST BANK FOR USING
ECONOMETRICS A PRACTICAL
GUIDE 6TH EDITION
STUDENMUND
, Answers to Text Exercises
Chapter One: An Overview of Regression Analysis
1-3. (a) Positive, (b) negative, (c) positive, (d) negative, (e) ambiguous, (f) negative.
1-4. (a) Customers number 3, 4, and 20; no.
(b) Weight is determined by more than just height.
(c) People who decide to play the weight-guessing game may feel they have a weight that is hard
to guess.
1-5. (a) The coefficients in the new equation are not the same as those estimated in the previous
equation because the sample is different. When the sample changes, so too can the estimated
coefficients. In particular, the constant term can change substantially between samples; in our
research for this exercise, for instance, we found one sample that had a negative intercept
(and a very steep slope).
(b) Equation 1.21 has the steeper slope (6.38 4.30) while Equation 1.24 has the greater
intercept (125.1 103.4). They intersect at 9.23 inches above 5 feet (162.3 pounds).
(c) Equation 1.24 misguesses by more than 10 pounds on exactly the same three observations
that Equation 1.21 does, but the sum of the squared residuals is greater for Equation 1.24 than
for Equation 1.21. This is not a surprise, because the coefficients of Equation 1.21 were
calculated using these data.
(d) If it were our last day on the job, we’d probably use an equation that we’d calculate from both
equations by taking the mean, or by taking an average weighted by sample size, of the two.
1-6. (a) The coefficient of Li represents the change in the percentage chance of making a putt
when the length of the putt increases by 1 foot. In this case, the percentage chance of making
the putt decreases by 4.1 for each foot longer the putt is.
Pˆ
(b) The equations are identical. To convert one to the other, note that i Pi e ,i which is true
ˆ ˆ
because ei Pi P i (or more generally, ei Yi Y ). i
(c) 42.6 percent, yes; 79.5 percent, no (too low); 18.9 percent, no (negative!).
(d) One problem is that the theoretical relationship between the length of the putt and the
percentage of putts made is almost surely nonlinear in the variables; we’ll discuss models
appropriate to this problem in Chapter 7. A second problem is that the actual dependent
variable is limited by zero and one but the regression estimate is not; we’ll discuss models
appropriate to this problem in Chapter 13.
ECONOMETRICS A PRACTICAL
GUIDE 6TH EDITION
STUDENMUND
, Answers to Text Exercises
Chapter One: An Overview of Regression Analysis
1-3. (a) Positive, (b) negative, (c) positive, (d) negative, (e) ambiguous, (f) negative.
1-4. (a) Customers number 3, 4, and 20; no.
(b) Weight is determined by more than just height.
(c) People who decide to play the weight-guessing game may feel they have a weight that is hard
to guess.
1-5. (a) The coefficients in the new equation are not the same as those estimated in the previous
equation because the sample is different. When the sample changes, so too can the estimated
coefficients. In particular, the constant term can change substantially between samples; in our
research for this exercise, for instance, we found one sample that had a negative intercept
(and a very steep slope).
(b) Equation 1.21 has the steeper slope (6.38 4.30) while Equation 1.24 has the greater
intercept (125.1 103.4). They intersect at 9.23 inches above 5 feet (162.3 pounds).
(c) Equation 1.24 misguesses by more than 10 pounds on exactly the same three observations
that Equation 1.21 does, but the sum of the squared residuals is greater for Equation 1.24 than
for Equation 1.21. This is not a surprise, because the coefficients of Equation 1.21 were
calculated using these data.
(d) If it were our last day on the job, we’d probably use an equation that we’d calculate from both
equations by taking the mean, or by taking an average weighted by sample size, of the two.
1-6. (a) The coefficient of Li represents the change in the percentage chance of making a putt
when the length of the putt increases by 1 foot. In this case, the percentage chance of making
the putt decreases by 4.1 for each foot longer the putt is.
Pˆ
(b) The equations are identical. To convert one to the other, note that i Pi e ,i which is true
ˆ ˆ
because ei Pi P i (or more generally, ei Yi Y ). i
(c) 42.6 percent, yes; 79.5 percent, no (too low); 18.9 percent, no (negative!).
(d) One problem is that the theoretical relationship between the length of the putt and the
percentage of putts made is almost surely nonlinear in the variables; we’ll discuss models
appropriate to this problem in Chapter 7. A second problem is that the actual dependent
variable is limited by zero and one but the regression estimate is not; we’ll discuss models
appropriate to this problem in Chapter 13.
