Principles of Managerial Statistics and Data Science

Appendix DSolutions to Odd‐Numbered Problems

Chapter 2

1. 2.1 (a) Legal sales (in $). (b) 1857. (c) $14 983.
2. 2.3 (b) They may not be representative of the population of interest.
3. 2.7 (a) Unstructured. (b) Unstructured. (c) Structured.
4. 2.9 (a) Ordinal. (b) Nominal. (c) Ordinal. (d) Nominal.
5. 2.11 (a) Discrete. (b) Continuous. (c) Continuous.
6. 2.13 Categorical and the level of measurement ordinal, but can also be interpreted as coming from a count of runners getting to finish line. However, some mathematical operations (e.g. the mean place) do not make sense.
7. 2.15 (a) Ratio. (b) Interval. (c) Ratio. (d) Interval. (e) Ratio.
8. 2.17 (a) A professional directory of all medical doctors. (b) Proportion of doctors who have been involved in a malpractice lawsuit. (c) 100 doctors who have been selected at random from a professional directory. (d) Proportion of doctors who have been involved in a malpractice lawsuit, in the sample of 100.
9. 2.19 Parameter, because it is the true measure of interest, and a statistic is a random estimate of the parameter.
10. 2.21 (a) Primary. (b) Primary. (c) Secondary.
11. 2.23 (a) Experimental. (b) Observational. (c) Observational. (d) Experimental.
12. 2.25 A discrete variable has countable number of distinct values, whereas a continuous variable can have any value in a given range or interval. Examples: number of cars (discrete), car speed (continuous).
13. 2.27 (a) Secondary. (b) Primary.
14. 2.29 (a) No. (b) No.
15. 2.31 (a) No. (b) Yes. (c) Yes.
16. 2.33 (a) Is there an increasing ...