- includes Online Content Printed Access Card
- Gerald Keller Wilfrid Laurier University
- ISBN-10: 0538477490
- ISBN-13: 9780538477499
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Instructor’s Solutions Manual
for
Statistics
for Management and Economics
Ninth Edition
Prepared by
Gerald
Keller
Wilfrid Laurier University
TABLE OF CONTENTS
How the Solutions
Were Produced 1
Chapter 1: What is
Statistics? 3
Chapter 2:
Graphical Descriptive Techniques I 5
Chapter 3: Graphical
Descriptive Techniques II 37
Chapter 4:
Numerical Descriptive Techniques 105
Chapter 5: Data
Collection and Samplin g 153
Chapter 6:
Probability 157
Chapter 7: Random
Variables and Discrete Probability Distributions 187
Chapter 8:
Continuous Probability Distributions 215
Chapter 9:
Sampling Distributions 229
Chapter 10: Introduction to Estimation 239
Chapter 11:
Introduction to Hypothesis Testing 247
Chapter 12:
Inference about One Population 269
Chapter 13:
Inference about Two Populations 313
Appendix 13 Review
of Chapters 12 and 13 375
Chapter 14: Analysis
of Variance 393
Appendix 14 Review of chapters 12 to 14 483
Chapter 15:
Chi-Squared Tests 457
Appendix 15 Review
of Chapters 12 to 15 493
Chapter 16 Simple
Linear Regression 509
Appendix 16 Review
of Chapters 12 to 16 565
Chapter 17:
Multiple Regression 593
Appendix 17 Review
of Chapters 12 to 17 649
Chapter 18: Model
Building 671
Chapter 19:
Nonparametric Statistical Techniques 707
Appendix 19 Review
of Chapters 12 to 19 761
Chapter 20 Time-Series
Analysis and Forecasting 793
Chapter 21
Statistical Process Control 815
Chapter 22: Decision
Analysis 843
Chapter 2
2.1 Nominal: Occupation, undergraduate major.
Ordinal: Rating of university professor, Taste test ratings. Interval: age,
income
2.2 a Interval
b Interval
c Nominal
d Ordinal
2.3 a Interval
b Nominal
c Ordinal
d Interval
e Interval
2.4 a Nominal
b Interval
c Nominal
d Interval
e Ordinal
2.5 a Interval
b Interval
c Nominal
d Interval
e Nominal
2.6 a Interval
b Interval
c Nominal
d Ordinal
e Interval
2.7 a Interval
b Nominal
c. Nominal
d Interval
e Interval
f Ordinal
2.8 a Interval
b Ordinal
c Nominal
d Ordinal
2.9 a Interval
b Nominal
c Nominal
2.10 a Ordinal
b Ordinal
c Ordinal
TEst bank for
CHAPTER 23: CONCLUSION
TRUE/FALSE
1. The same statistical techniques apply whether
the data is interval, nominal, or ordinal.
ANS: F PTS: 1 NAT: Analytic; Statistical Inference
2. The source of statistical inference is the
sampling distribution.
ANS: T PTS: 1 NAT: Analytic; Statistical Inference
3. The validity of any statistical outcome
depends on the validity of its sample.
ANS: T PTS: 1 NAT: Analytic; Statistical Inference
4. Statistical inferences are facts and are not
based on probability.
ANS: F PTS: 1 NAT: Analytic; Statistical Inference
5. In hypothesis testing, you start out assuming
the null hypothesis is false.
ANS: F PTS: 1 NAT: Analytic; Statistical Inference
6. If the difference between the null hypothesis
and your test statistic is very large, you reject the null hypothesis.
ANS: T PTS: 1 NAT: Analytic; Statistical Inference
7. If the probability of making a Type II error
decreases, the probability of making a Type I error increases.
ANS: T PTS: 1 NAT: Analytic; Statistical Inference
8. A procedure with a very small probability of
a Type I error will also have a very small probability of a Type II error.
ANS: F PTS: 1 NAT: Analytic; Statistical Inference
9. A larger sample increases the confidence
level of a confidence interval.
ANS: F PTS: 1 NAT: Analytic; Statistical Inference
10. We can use analysis of variance (ANOVA) in
place of the t-test when comparing two population means.
ANS: T PTS: 1 NAT: Analytic; Statistical Inference
11. The Student-t and the F-distributions
have no relationship to each other.
ANS: F PTS: 1 NAT: Analytic; Statistical Inference
12. We can use regression analysis with indicator
variables in place of analysis of variance (ANOVA).
ANS: T PTS: 1 NAT: Analytic; Statistical Inference
13. The techniques used to analyze nominal data
involve a ranking procedure.
ANS: F PTS: 1 NAT: Analytic; Statistical Inference
14. The techniques used to analyze ordinal data
involve a ranking procedure.
ANS: T PTS: 1 NAT: Analytic; Statistical Inference
15. The standard normal distribution and the
Chi-squared distribution are related to each other.
ANS: T PTS: 1 NAT: Analytic; Statistical Inference
MULTIPLE CHOICE
16. If you use information about a sample to draw
a conclusion about a population, you are doing:
|
a.
|
Inferential parameters
|
|
b.
|
Descriptive statistics
|
|
c.
|
Inferential statistics
|
|
d.
|
The wrong kind of statistics
|
ANS: C PTS: 1 NAT: Analytic; Statistical Inference
17. Which of the following is NOT a type of data?
|
a.
|
Parameter data
|
|
b.
|
Nominal data
|
|
c.
|
Ordinal data
|
|
d.
|
Interval data
|
ANS: A PTS: 1 NAT: Analytic; Statistical Inference
18. Which type of data involves real numbers?
|
a.
|
Nominal data
|
|
b.
|
Interval data
|
|
c.
|
Ordinal data
|
|
d.
|
None of these choices.
|
ANS: B PTS: 1 NAT: Analytic; Statistical Inference
19. Which type of data involves categories?
|
a.
|
Interval data
|
|
b.
|
Ordinal data
|
|
c.
|
Nominal data
|
|
d.
|
None of these
|
ANS: C PTS: 1 NAT: Analytic; Statistical Inference
20. Which type of data involves ratings?
|
a.
|
Interval data
|
|
b.
|
Ordinal data
|
|
c.
|
Nominal data
|
|
d.
|
None of these
|
ANS: B PTS: 1 NAT: Analytic; Statistical Inference
21. Which of the following is an example of
interval data?
|
a.
|
The weight of a newborn baby.
|
|
b.
|
The gender of a baby.
|
|
c.
|
Whether or not a baby weighs more than 10
pounds.
|
|
d.
|
Your order of preference of three baby
names.
|
ANS: A PTS: 1 NAT: Analytic; Statistical Inference
22. Which of the following statements is true?
|
a.
|
Descriptive techniques summarize
information from samples.
|
|
b.
|
Inferential techniques allow us to make
estimates about a population.
|
|
c.
|
Inferential techniques allow us to draw
conclusions about a population.
|
|
d.
|
All of these statements are true.
|
ANS: D PTS: 1 NAT: Analytic; Statistical Inference
23. Which of the following is an example of
nominal data?
|
a.
|
The gender of a baby.
|
|
b.
|
The weight of a newborn baby.
|
|
c.
|
The number of other babies born on the same
day.
|
|
d.
|
Your order of preference of three baby
names.
|
ANS: A PTS: 1 NAT: Analytic; Statistical Inference
24. Which of the following is an example of
ordinal data?
|
a.
|
The weight of a newborn baby.
|
|
b.
|
The gender of a baby.
|
|
c.
|
The number of siblings a baby has.
|
|
d.
|
Your order of preference of three baby
names.
|
ANS: D PTS: 1 NAT: Analytic; Statistical Inference
25. How do the requirements of nonparametric and
parametric techniques compare?
|
a.
|
Nonparametric techniques have more
restrictions than parametric techniques.
|
|
b.
|
Nonparametric techniques have fewer
restrictions than parametric techniques.
|
|
c.
|
Both types of techniques have the same
requirements.
|
|
d.
|
There are no requirements for parametric or
nonparametric techniques.
|
ANS: B PTS: 1 NAT: Analytic; Statistical Inference
26. If your hypothesis test has a very small
probability for a Type I error, how does this affect the probability of a Type
II error?
|
a.
|
It will increase.
|
|
b.
|
It will decrease.
|
|
c.
|
It will be the same as for a Type I error.
|
|
d.
|
No way of knowing without more information.
|
ANS: A PTS: 1 NAT: Analytic; Statistical Inference
27. The sampling distributions that are used for
interval data are the Student-t and the:
|
a.
|
Chi-squared distribution.
|
|
b.
|
Binomial distribution.
|
|
c.
|
Discrete distribution.
|
|
d.
|
F-distribution.
|
ANS: D PTS: 1 NAT: Analytic; Statistical Inference
28. The sampling distributions that are used for
nominal data are the standard normal distribution and the:
|
a.
|
Chi-squared distribution.
|
|
b.
|
Binomial distribution.
|
|
c.
|
F-distribution.
|
|
d.
|
Interval distribution.
|
ANS: A PTS: 1 NAT: Analytic; Statistical Inference
29. Which of the following data collection
methods is more likely to lead to a definitive conclusion?
|
a.
|
Data collected through observation.
|
|
b.
|
Data collected through an experiment.
|
|
c.
|
Data collected through the use of
volunteers.
|
|
d.
|
Data collected through a survey.
|
ANS: B PTS: 1 NAT: Analytic; Statistical Inference
COMPLETION
30. ____________________ techniques allow us to
make estimates and draw conclusions about populations from samples.
ANS: Inferential
PTS: 1 NAT: Analytic; Statistical Inference
31. There are three types of data:
____________________; ____________________; and ____________________.
ANS:
interval; nominal; ordinal
interval; ordinal; nominal
nominal; interval; ordinal
nominal; ordinal; interval
ordinal; interval; nominal
ordinal; nominal; interval
PTS: 1 NAT: Analytic; Statistical Inference
32. If the difference between our test statistic
and the null hypothesis is large, we reject the ____________________
hypothesis.
ANS: null
PTS: 1 NAT: Analytic; Statistical Inference
33. The standard that we use to decide whether or
not to reject a null hypothesis is the probability of a(n)
____________________.
ANS: Type I error
PTS: 1 NAT: Analytic; Statistical Inference
34. In any hypothesis test there are two possible
errors, called ____________________ and ____________________.
ANS:
Type I; Type II
Type II; Type I
Type I errors; Type II errors
Type II errors; Type I errors
PTS: 1 NAT: Analytic; Statistical Inference
35. Formulas for confidence intervals and test
statistics all come from ____________________ distributions.
ANS: sampling
PTS: 1 NAT: Analytic; Statistical Inference
36. We can improve the exactitude of a confidence
interval estimator by increasing the ____________________.
ANS: sample size
PTS: 1 NAT: Analytic; Statistical Inference
37. We can decrease the probability of a Type II
error by increasing the ____________________.
ANS: sample size
PTS: 1 NAT: Analytic; Statistical Inference
38. The width of a confidence interval
____________________ when more data is collected.
ANS: decreases
PTS: 1 NAT: Analytic; Statistical Inference
39. In analyzing interval data, we attempt to
explain as much of the ____________________ as possible.
ANS: variation
PTS: 1 NAT: Analytic; Statistical Inference
40. The techniques used on ordinal data are based
on ranking procedures. We call these ____________________ techniques.
ANS: nonparametric
PTS: 1 NAT: Analytic; Statistical Inference
41. To ensure the validity of a statistical
technique, we must first check the required ____________________.
ANS: conditions
PTS: 1 NAT: Analytic; Statistical Inference
42. We often use a(n) ____________________
technique to analyze data when the conditions for a(n) ____________________
technique are not satisfied.
ANS: nonparametric; parametric
PTS: 1 NAT: Analytic; Statistical Inference
43. Two ways in which we can obtain data are
through ____________________ or ____________________.
ANS:
experimentation; observation
observation; experimentation
PTS: 1 NAT: Analytic; Statistical Inference
SHORT ANSWER
44. Describe a plan for estimating the average
GPA at your university by using inferential statistics. Include which
statistical technique you plan to use to draw your conclusions.
ANS:
Select a random sample of n students from
this university, where n is large. Find the GPA for each student, and
then calculate the mean and standard deviation of the GPA for all n students.
Use this information to estimate the average GPA for all students at the
university by using a confidence interval.
PTS: 1 NAT: Analytic; Statistical Inference
45. One prevailing idea amongst statisticians is
the idea of "Garbage in / garbage out." Explain the meaning of this
phrase and give an example of it.
ANS:
The validity of any statistical result or
conclusion depends on the validity of the sampling procedure, and the data
collection process.
Example: A researcher wants to determine which candidate is being
favored in the next presidential election, so she goes to the mall on Saturday
and asks the first 100 people she sees. Her results are not credible because
she used a biased sample.
PTS: 1 NAT: Analytic; Statistical Inference
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