, Chapter 1
1.2 Descriptive techniques summarize data. Inferential techniques draw inferences about a population based on
sample data.
1.3 a The population is the 25,000 registered voters.
b The sample is the 200 registered voters.
c The 48% figure is the statistic
1.4 a The population is the complete production run.
b The sample is comprised of the 1,000 chips.
c The parameter is the proportion of defective chips in the production run.
d The statistic is the proportion of defective chips in the sample.
e The 10% figure refers to the parameter.
f The 7.5% figure refers to the statistic.
g We can estimate the population proportion is 7.5%. Statistical inference methods will allow us to determine
whether we have enough statistical evidence to reject the claim.as the sample proportion.
1.5 Draw a random sample from the population of graduates who have majored in your subject and a random sample
of graduates of other majors and record their highest salary offers.
1.6 a Flip the coin (say 100 times) and record the number of heads (assuming that you are interested in the number
of heads).
b The population is composed of the theoretical result of flipping the coin an infinite number of times and recording
either “heads” or “tails”.
c The sample is comprised of the “heads” and “tails” in the sample.
d The parameter is the proportion of heads (again assuming that your interest is the number of heads rather than
tails) in the population.
e The statistic is the proportion of heads (or tails depending on the choice made in part d).
f The sample statistic can be used to judge whether the coin is actually fair.
1.7 a We would conclude that the coin is not fair.
b We may conclude that there is some evidence that the coin is not fair.
1.8 a The population is made up of the propane mileage of all the cars in the fleet.
b The parameter is the mean propane mileage of all the cars in the fleet.
c The sample is composed of the propane mileage of the 50 cars.
,d The statistic is the mean propane mileage of the 50 cars in the sample.
e We can use the sample statistic to estimate the population parameter.
, 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
5
1.2 Descriptive techniques summarize data. Inferential techniques draw inferences about a population based on
sample data.
1.3 a The population is the 25,000 registered voters.
b The sample is the 200 registered voters.
c The 48% figure is the statistic
1.4 a The population is the complete production run.
b The sample is comprised of the 1,000 chips.
c The parameter is the proportion of defective chips in the production run.
d The statistic is the proportion of defective chips in the sample.
e The 10% figure refers to the parameter.
f The 7.5% figure refers to the statistic.
g We can estimate the population proportion is 7.5%. Statistical inference methods will allow us to determine
whether we have enough statistical evidence to reject the claim.as the sample proportion.
1.5 Draw a random sample from the population of graduates who have majored in your subject and a random sample
of graduates of other majors and record their highest salary offers.
1.6 a Flip the coin (say 100 times) and record the number of heads (assuming that you are interested in the number
of heads).
b The population is composed of the theoretical result of flipping the coin an infinite number of times and recording
either “heads” or “tails”.
c The sample is comprised of the “heads” and “tails” in the sample.
d The parameter is the proportion of heads (again assuming that your interest is the number of heads rather than
tails) in the population.
e The statistic is the proportion of heads (or tails depending on the choice made in part d).
f The sample statistic can be used to judge whether the coin is actually fair.
1.7 a We would conclude that the coin is not fair.
b We may conclude that there is some evidence that the coin is not fair.
1.8 a The population is made up of the propane mileage of all the cars in the fleet.
b The parameter is the mean propane mileage of all the cars in the fleet.
c The sample is composed of the propane mileage of the 50 cars.
,d The statistic is the mean propane mileage of the 50 cars in the sample.
e We can use the sample statistic to estimate the population parameter.
, 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
5
