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Sampling: Design and Analysis 3rd Edition by Sharon L. Lohr | Chapters 1-16 | SOLUTIONS MANUAL €29,99
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Sampling: Design and Analysis 3rd Edition by Sharon L. Lohr | Chapters 1-16 | SOLUTIONS MANUAL

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SOLUTIONS MANUAL for Sampling: Design and Analysis 3rd Edition by Sharon L. Lohr | Complete Chapters 1-16.1. Introduction 2. Simple Probability Samples 3. Stratified Sampling 4. Ratio and Regression Estimation 5. Cluster Sampling with Equal Probabilities 6. Sampling with Unequal Probabilities 7. C...

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,
,2 CHAPTER 1. INTRODUCTION

opinions. Indeed, there have been instances where authors of competing books have written negative
reviews of a book, or a book’s author manages to flood the site with positive reviews.

1.4 Target population: Persons eligible for jury duty in Pennsylvania.
Sampling frame: State residents who are registered voters or licensed drivers over 18.
Sampling unit = observation unit: One resident.

Selection bias occurs largely because of undercoverage and nonresponse. Eligible jurors may not
appear in the sampling frame because they are not registered to vote and they do not possess an
Arizona driver’s license. Addresses on either list may not be up to date. In addition, jurors fail to
appear or are excused; this is nonresponse.

1.5 Target population: All persons experiencing homelessness in study area.
Sampling frame: Clinics participating in the Health Care for the Homeless project.
Sampling unit: Unclear. Depending on assumptions made about the survey design, one could say
either a clinic or a person is the sampling unit.
Observation unit: Person.

Selection bias may be a serious problem for this survey. Even though the demographics for HCH
patients are claimed to match those of the homeless population (but do we know they match?)
and the clinics are readily accessible, the patients differ in two critical ways from non-patients:
(1) they needed medical treatment, and (2) they went to a clinic to get medical treatment. One
does not know the likely direction of selection bias, but there is no reason to believe that the same
percentages of patients and non-patients are mentally ill.

1.6 Target population: Likely voters in Iowa.
Sampling frame: Persons who attend the State Fair and stop by the booth.
Sampling unit = observation unit: One person.

This is a convenience sample of volunteers, and we cannot trust any statistics from it.

1.7 Target population: All cows in region.
Sampling frame: List of all farms in region.
Sampling unit: One farm.
Observation unit: One cow.

There is no reason to anticipate selection bias in this survey. The design is a single-stage cluster
sample, discussed in Chapter 5.

1.8 Target population: Licensed boarding homes for the elderly in Washington state.
Sampling frame: List of 184 licensed homes.
Sampling unit = observation unit: One home.

, 3

Nonresponse is the obvious problem here, with only 43 of 184 administrators or food service man-
agers responding. It may be that the respondents are the larger homes, or that their menus have
better nutrition. The problem with nonresponse, though, is that we can only conjecture the direc-
tion of the nonresponse bias.

1.9 Target population: Wikipedia science articles.
Sampling frame: Articles thought to be of interest by the sampler.
Sampling unit: One article.

This is a judgment sample, where the articles are deliberately chosen for review. The statistics
apply only to the sample, and cannot be generalized to the population. There is additional possible
selection bias because of the nonresponse; perhaps articles with many or few errors are harder to
get reviewers for.

1.10 Target population: The 32,000 subscribers to the magazine.
Sampling frame: Magazine subscribers who saw the survey invitation.
Sampling unit: One response. Since more than 32,000 responses were received, it appears that
either non-subscribers responded to the survey or some subscribers responded multiple times.

This is a convenience sample. The statistics have no validity because of the self-selected nature of
the sample. A person who responded multiple times could unduly influence the survey results. In
many surveys of this type, only persons with strong opinions respond. It’s possible in this case that
persons who have been inconvenienced by a PC malfunction will be more likely to respond than
persons who have experienced no problems with their PCs.

1.11 Target population: Unclear. Presumably they want to generalize the results to adult women.
Sampling frame: Persons who see and respond to the online invitation.
Sampling unit: One response. It is possible that some persons responded multiple times.

This is a convenience sample. The statistics have no validity because of the self-selected nature of
the sample. We don’t even know if 4,000 different women responded, or even if the respondents are
women; it could be just a handful of persons each responding multiple times.

1.12 Target population: Faculty members at higher education institutions.
Sampling frame: Faculty members in the purposively sampled institutions. The authors did not
state how they selected the faculty in those institutions who were surveyed.
Sampling unit: One faculty member.

There are several sources of selection bias. The first is the purposive nature of the college sample.
Although the authors stated that the institutions are “representative in terms of institutional type,
geographic and demographic diversity, religious/nonreligious affiliation, and the public/private di-
mension,” it is very easy for conscious or unconscious subjective biases to skew such a sample.
A second source of potential bias comes from the selection of faculty to participate (if not every-

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