SOLLUTIONS MANUAL
STATISTICAL REASONING FOR EVERYDAY LIFE
6TH EDITION
CHAPTER NO. 01: SPEAKING OF STATISTICS
SECTION 1.1: WHAT IS/ARE STATISTICS
1. The two meanings are: (1) statistics is the science of collecting, organizing, and
interpreting data; and (2) statistics are the data (numbers or other pieces of information)
that describe or summarize some characteristic from a sample. Note that for the first
meaning, the word “statistics” is singular and for the second it is plural.
2. A population is the complete set of people or things being studied, while a sample is a
subset of a population. In other words, the sample is only a part of the complete
population. A population parameter is a characteristic of a population. A sample statistic is a
characteristic of a sample found by consolidating or summarizing raw data. Raw data are
all measurements or observations collected. It is usually impractical to directly measure
population parameters for large populations, so we usually infer likely values of the
population parameters from the measured sample statistics.
3. The margin of error is used to describe the range of values in a confidence interval.
We add and subtract the margin of error from a sample statistic to find the confidence
interval, or the range of values that is likely to contain some population parameter. The
confidence interval is used to estimate the population parameter, and the confidence level
(e.g., 95%) tells us how confident we should be that the population parameter lies within
the quoted range.
4. The basic steps, summarized in Figure 1.1, are: (1) identify the goals; (2) choose a
representative sample from the population; (3) collect raw data from the sample and
summarize them with sample statistics; (4) use the sample statistics to make inferences
about the population; (5) draw conclusions from your results. Students should come up
with their own example.
5. This statement does not make sense. Samples are drawn from a population, so the
size of a sample is always less than or equal to the size of the population.
,6. This statement makes sense. The margin of error suggests a (presumably 95%)
confidence interval from 52% to 58%. However, there is always some chance that the
actual population proportion is outside the confidence interval, and in this case it would
not need to be far outside for the candidate to lose. Moreover, the poll was taken 2 months
before the election, and voters may change their minds by election time.
7. This statement does not make sense. A margin of error of zero would imply that there
is no uncertainty in a survey result, and that could happen only if the entire population
was surveyed, rather than just a sample.
8. This statement makes sense. The confidence interval of 55% to 65% is an estimate
that could be wrong. There is no guarantee that the percentage in favor of the candidate
is greater than 50%.
9. This statement does not make sense. Inferences about one population (males) do not
necessarily apply to a different population (females).
10. This statement does not make sense. The correct margin of error is half of the
confidence range, which in this case is (70%− 60%) 2 = 5 percentage points.
CONCEPTS AND APPLICATIONS
11. Sample: the 30,000 adults who were surveyed. Population: the complete set of all
adult Americans. Sample statistic: 12.5%. The value of the population parameter is not
known, but it is the percentage of all adult Americans who smoked one or more cigarettes
in the past week.
12. Sample: the 106 body temperatures collected in the study. Population: the complete
set of all adults. Sample statistic: 98.2°F. The value of the population parameter is not
known, but it is the average (mean) body temperature of all adults.
13. Sample: the 47 subjects treated with Garlicin. Population: the complete set of all
adults. Sample statistic: 3.2mg/dL. The value of the population parameter is not known,
but it is the average (mean) change in LDL cholesterol.
14. Sample: the 150 senior executives who were surveyed. Population: the complete set
of all senior executives. Sample statistic: 47%. The value of the population parameter is
not known, but it is the percentage of all senior executives who say that the most common
job interview mistake is to have little or no knowledge of the company where the applicant
is being interviewed.
,15. The range of values likely to contain the true value of the population parameter is from
77%− 2% to 77%+ 2% or from 75% to 79%.
16. The range of values likely to contain the true value of the population parameter is from
85%−1% to 85%+1% or from 84% to 86%.
17. The range of values likely to contain the true value of the population parameter is from
15%−1% to 15%+1% or from 14% to 16%.
18. The range of values likely to contain the true value of the population parameter (mean
body temperature) is 98.2°F − 0.1°F to 98.2°F + 0.1°F or from 98.1°F to 98.3°F degrees.
19. The range of values likely to contain the true value of the population parameter is from
57%− 4% to 57%+ 4% or from 53% to 61%.
20. The range of values likely to contain the true value of the population parameter is from
3152g − 68g to 3152g + 68g or from 3084 grams to 3220 grams.
21. Based on the survey, the actual percentage of voters is expected to be between 67%
and 73%, which does not include the 61% value from actual voting records. If the survey
was conducted well, then it is unlikely that its result would be so different from the actual
voter turnout, implying either that respondents intentionally lied to appear favorable to the
pollsters or that their memories may have been faulty.
22. It appears that the men who were surveyed may have been influenced by the gender
of the interviewer. When they were interviewed by women, they may have been more
inclined to respond in a way that they thought was more favorable to the female
interviewers.
23. Yes, we can safely conclude that fewer than half of all students say they are tired on
most days. Based on the confidence interval and margin of error, it is likely that the actual
population parameter is fairly close to the 39% sample statistic, and very unlikely that the
true value could be above 50%.
24. No, the results do not contradict Mendel’s theory. Using the margin of error, it appears
that the percentage of yellow peas is likely to be between 22% and 30%, and that range
of values includes Mendel’s claimed value of 25%, so the results do not contradict his
theory.
, 25. a) Goal: determine the percentage of employees who would like to have their boss’s
job. Population: the complete set of all employees. Population parameter: the percentage
of all employees who would like to have their boss’s job.
b) Sample: the 144 employees selected for the survey. Raw data: individual responses
to the question. Sample statistic: 21%.
c) The range of values likely to contain the population parameter is from 21%− 7% = 14%
to 21%+ 7% = 28%.
26. a) Goal: determine the percentage of all human resource professionals who say that
the appearance of a job applicant is most important for a good first impression.
Population: the complete set of all human resource professionals. Population parameter:
the percentage of all human resource professionals who say that the appearance of a job
applicant is the single most important factor in making a good first impression.
b) Sample: the 514 human resource professionals who were surveyed. Raw data: the
responses from the 514 human resource professionals selected for the survey. Sample
statistic: 90%.
c) The range of values likely to contain the population parameter is from 90%− 2.5%
= 87.5% to 90%+ 2.5% = 92.5%.
27. a) Goal: determine the percentage of adults who say that they are underpaid.
Population: the complete set of all adults. Population parameter: the percentage of all
adults who say that they are underpaid.
b) Sample: the 557 adults randomly selected and surveyed. Raw data: individual
responses to the survey question. Sample statistic: 51%.
c) The range of values likely to contain the population parameter is 51%− 4% = 47% to
51%+ 4% = 55%.
28. a) Goal: determine the percentage of all patients given Eliquis who develop nausea.
Population: the complete set of all patients treated with Eliquis. Population parameter: the
percentage of patients treated with Eliquis who develop nausea.
b) Sample: the 5924 patients treated with Eliquis. Raw data: the number of those 5924
patients who developed nausea. Sample statistic: 2.6%.
STATISTICAL REASONING FOR EVERYDAY LIFE
6TH EDITION
CHAPTER NO. 01: SPEAKING OF STATISTICS
SECTION 1.1: WHAT IS/ARE STATISTICS
1. The two meanings are: (1) statistics is the science of collecting, organizing, and
interpreting data; and (2) statistics are the data (numbers or other pieces of information)
that describe or summarize some characteristic from a sample. Note that for the first
meaning, the word “statistics” is singular and for the second it is plural.
2. A population is the complete set of people or things being studied, while a sample is a
subset of a population. In other words, the sample is only a part of the complete
population. A population parameter is a characteristic of a population. A sample statistic is a
characteristic of a sample found by consolidating or summarizing raw data. Raw data are
all measurements or observations collected. It is usually impractical to directly measure
population parameters for large populations, so we usually infer likely values of the
population parameters from the measured sample statistics.
3. The margin of error is used to describe the range of values in a confidence interval.
We add and subtract the margin of error from a sample statistic to find the confidence
interval, or the range of values that is likely to contain some population parameter. The
confidence interval is used to estimate the population parameter, and the confidence level
(e.g., 95%) tells us how confident we should be that the population parameter lies within
the quoted range.
4. The basic steps, summarized in Figure 1.1, are: (1) identify the goals; (2) choose a
representative sample from the population; (3) collect raw data from the sample and
summarize them with sample statistics; (4) use the sample statistics to make inferences
about the population; (5) draw conclusions from your results. Students should come up
with their own example.
5. This statement does not make sense. Samples are drawn from a population, so the
size of a sample is always less than or equal to the size of the population.
,6. This statement makes sense. The margin of error suggests a (presumably 95%)
confidence interval from 52% to 58%. However, there is always some chance that the
actual population proportion is outside the confidence interval, and in this case it would
not need to be far outside for the candidate to lose. Moreover, the poll was taken 2 months
before the election, and voters may change their minds by election time.
7. This statement does not make sense. A margin of error of zero would imply that there
is no uncertainty in a survey result, and that could happen only if the entire population
was surveyed, rather than just a sample.
8. This statement makes sense. The confidence interval of 55% to 65% is an estimate
that could be wrong. There is no guarantee that the percentage in favor of the candidate
is greater than 50%.
9. This statement does not make sense. Inferences about one population (males) do not
necessarily apply to a different population (females).
10. This statement does not make sense. The correct margin of error is half of the
confidence range, which in this case is (70%− 60%) 2 = 5 percentage points.
CONCEPTS AND APPLICATIONS
11. Sample: the 30,000 adults who were surveyed. Population: the complete set of all
adult Americans. Sample statistic: 12.5%. The value of the population parameter is not
known, but it is the percentage of all adult Americans who smoked one or more cigarettes
in the past week.
12. Sample: the 106 body temperatures collected in the study. Population: the complete
set of all adults. Sample statistic: 98.2°F. The value of the population parameter is not
known, but it is the average (mean) body temperature of all adults.
13. Sample: the 47 subjects treated with Garlicin. Population: the complete set of all
adults. Sample statistic: 3.2mg/dL. The value of the population parameter is not known,
but it is the average (mean) change in LDL cholesterol.
14. Sample: the 150 senior executives who were surveyed. Population: the complete set
of all senior executives. Sample statistic: 47%. The value of the population parameter is
not known, but it is the percentage of all senior executives who say that the most common
job interview mistake is to have little or no knowledge of the company where the applicant
is being interviewed.
,15. The range of values likely to contain the true value of the population parameter is from
77%− 2% to 77%+ 2% or from 75% to 79%.
16. The range of values likely to contain the true value of the population parameter is from
85%−1% to 85%+1% or from 84% to 86%.
17. The range of values likely to contain the true value of the population parameter is from
15%−1% to 15%+1% or from 14% to 16%.
18. The range of values likely to contain the true value of the population parameter (mean
body temperature) is 98.2°F − 0.1°F to 98.2°F + 0.1°F or from 98.1°F to 98.3°F degrees.
19. The range of values likely to contain the true value of the population parameter is from
57%− 4% to 57%+ 4% or from 53% to 61%.
20. The range of values likely to contain the true value of the population parameter is from
3152g − 68g to 3152g + 68g or from 3084 grams to 3220 grams.
21. Based on the survey, the actual percentage of voters is expected to be between 67%
and 73%, which does not include the 61% value from actual voting records. If the survey
was conducted well, then it is unlikely that its result would be so different from the actual
voter turnout, implying either that respondents intentionally lied to appear favorable to the
pollsters or that their memories may have been faulty.
22. It appears that the men who were surveyed may have been influenced by the gender
of the interviewer. When they were interviewed by women, they may have been more
inclined to respond in a way that they thought was more favorable to the female
interviewers.
23. Yes, we can safely conclude that fewer than half of all students say they are tired on
most days. Based on the confidence interval and margin of error, it is likely that the actual
population parameter is fairly close to the 39% sample statistic, and very unlikely that the
true value could be above 50%.
24. No, the results do not contradict Mendel’s theory. Using the margin of error, it appears
that the percentage of yellow peas is likely to be between 22% and 30%, and that range
of values includes Mendel’s claimed value of 25%, so the results do not contradict his
theory.
, 25. a) Goal: determine the percentage of employees who would like to have their boss’s
job. Population: the complete set of all employees. Population parameter: the percentage
of all employees who would like to have their boss’s job.
b) Sample: the 144 employees selected for the survey. Raw data: individual responses
to the question. Sample statistic: 21%.
c) The range of values likely to contain the population parameter is from 21%− 7% = 14%
to 21%+ 7% = 28%.
26. a) Goal: determine the percentage of all human resource professionals who say that
the appearance of a job applicant is most important for a good first impression.
Population: the complete set of all human resource professionals. Population parameter:
the percentage of all human resource professionals who say that the appearance of a job
applicant is the single most important factor in making a good first impression.
b) Sample: the 514 human resource professionals who were surveyed. Raw data: the
responses from the 514 human resource professionals selected for the survey. Sample
statistic: 90%.
c) The range of values likely to contain the population parameter is from 90%− 2.5%
= 87.5% to 90%+ 2.5% = 92.5%.
27. a) Goal: determine the percentage of adults who say that they are underpaid.
Population: the complete set of all adults. Population parameter: the percentage of all
adults who say that they are underpaid.
b) Sample: the 557 adults randomly selected and surveyed. Raw data: individual
responses to the survey question. Sample statistic: 51%.
c) The range of values likely to contain the population parameter is 51%− 4% = 47% to
51%+ 4% = 55%.
28. a) Goal: determine the percentage of all patients given Eliquis who develop nausea.
Population: the complete set of all patients treated with Eliquis. Population parameter: the
percentage of patients treated with Eliquis who develop nausea.
b) Sample: the 5924 patients treated with Eliquis. Raw data: the number of those 5924
patients who developed nausea. Sample statistic: 2.6%.
