Bobby Smith

Ch. 1
1.12) (a) This could be misleading because car accidents could be caused by a lot more things other than smoking. The people that they look at could be notorious bad drivers who often get distracted. The numbers could also be skewed because they didn’t take into account age, gender, or maybe even race which could lead to more wrecks. It could also do with how well the driver can see or maybe even hear.
(b) There could be a causal link between smoking and car crashes, however, because the people who smoke may have been smoking while driving which can be distracting.
1.13) I don’t think it would be significant because it is such a low number.
1.14) (a) This isn’t a very logical conclusion because it’s only a small sample.
(b) This isn’t ethical because this could be misleading to their other customers because it’s only the opinion of a few people.
(c) This isn’t ethical because they don’t know if this could be harmful to those people.
(d) This isn’t logical because there is no causal effect between the incident and the verdict.
1.26) (a)
(b)
1.27) (a)
(b)
2.1) (a) Categorical
(b) Categorical
(c) Discrete
2.2) (a) Continuous
(b) Discrete
(c) Categorical
(d) Continuous

2.3) (a) Continuous
(b) Continuous
(c) Categorical
(d) Categorical
2.5) (a) Ratio
(b) Ordinal
(c) Nominal
(d) Interval
(e) Ratio
(f) Nominal
2.6) (a) Ratio
(b) Ratio
(c) Interval
(d) Nominal
(e) Interval
(f) Nominal
2.7) Nominal – The name of each player on a baseball roster.
Ordinal – Rating a player on a scale of 1-10
Interval – The temperature in Kelvins
Ratio – The number of players who have a base hit in a game
2.8) (a) Interval
(b) Interval
(c) Nominal
(d) Ratio

2.11) (a) Cross-sectional
(b) Time Series
(c) Time Series
(d) Cross-sectional
2.12) (a) Time Series
(b) Cross-sectional
(c) Time Series
(d) Cross-sectional
2.13)