Essentials Of Business Statistics, Bowerman - Exam Preparation Test Bank (Downloadable Doc)

Ch01
Student: ___________________________________________________________________________

1. A population is a set of existing units.
True False
2. If we examine some of the population measurements, we are conducting a census of the population.
True False
3. A random sample is selected so that every element in the population has the same chance of being
included in the sample.
True False
4. An example of a quantitative variable is the make of a car.
True False
5. An example of a qualitative variable is the mileage of a car.
True False
6. Statistical inference is the science of using a sample of measurements to make generalization about the
important aspects of a population of measurements.
True False
7. Time series data are data collected at the same time period.
True False
8. Cross-sectional data are data collected at the same point in time.
True False
9. Daily temperature in a local community collected over a 30-day time period is an example of cross-
sectional data.
True False
10. The number of sick days taken by employees in 2008 for the top 10 technology companies is an example
of time-series data.
True False
11. The number of sick days per month taken by employees for the last ten years at Apex Co. is an example
of time-series data.
True False
12. A quantitative variable can also be referred to as a categorical variable.
True False
13. In a data set of information on college business students, an example of an element is their cumulative
gpa.
True False
14. In an observational study, the variable of interest is called a response variable.
True False
15. In an experimental study, the aim is to manipulate or set the value of the response variable.
True False
16. The science of describing the important aspects of a set of measures is called statistical inference.
True False

,17. A practical method of selecting a random sample is to utilize a random number table.
True False
18. It is possible to use a random sample from one population to make statistical inferences about another
related population.
True False
19. Processes produce outputs over time.
True False
20. Ratio variables have the following characteristics:
A. Meaningful order
B. An inherently defined zero value
C. Categorical in nature
D. Predictable
21. Which of the following is a quantitative variable?
A. The make of a TV
B. A person's gender
C. Mileage of a car
D. Whether a person is a college graduate
E. Whether a person has a charge account
22. Which of the following is a categorical variable?
A. Air Temperature
B. Bank Account Balance
C. Daily Sales in a Store
D. Whether a Person Has a Traffic Violation
E. Value of Company Stock
23. Measurements from a population are called
A. Elements
B. Observations
C. Variables
D. Processes
24. The two types of quantitative variables are:
A. Ordinal and ratio
B. Interval and ordinal
C. Nominative and ordinal
D. Interval and ratio
E. Nominative and interval
25. Temperature (in degrees Fahrenheit) is an example of a(n) ________ variable.
A. Nominative
B. Ordinal
C. Interval
D. Ratio
26. Jersey numbers of soccer players is an example of a(n) ___________ variable.
A. Nominative
B. Ordinal
C. Interval
D. Ratio

,27. The weight of a chemical compound used in an experiment that is obtained using a well-adjusted scale
represents a(n) _____________ level of measurement.
A. Nominative
B. Ordinal
C. Interval
D. Ratio
28. An identification of police officers by rank would represent a(n) ____________ level of
measurement.
A. Nominative
B. Ordinal
C. Interval
D. Ratio
29. __________ is a necessary component of a runs plot.
A. Observation over time
B. Qualitative variable
C. Random sampling of the data
D. Cross sectional data
30. ______________ is the science of using a sample to make generalizations about the important aspects of
a population.
A. Time Series Analysis
B. Descriptive Statistics
C. Random sample
D. Statistical Inference
31. College entrance exam scores, such as SAT scores, are an example of a(n) ________________
variable.
A. Ordinal
B. Ratio
C. Nominative
D. Interval
32. The number of miles a truck is driven before it is overhauled is an example of a(n) _____________
variable.
A. Nominative
B. Ordinal
C. Interval
D. Ratio
33. A(n) ___________________ variable is a qualitative variable such that there is no meaningful ordering or
ranking of the categories.
A. Ratio
B. Ordinal
C. Nominative
D. Interval
34. A person's telephone area code is an example of a(n) _____________ variable.
A. Nominative
B. Ordinal
C. Interval
D. Ratio
35. Any characteristic of a population unit is a(n):
A. Measurement
B. Sample
C. Observation
D. Variable

, 36. Examining all population measurements is called a ____.
A. Census
B. Frame
C. Sample
D. Variable
37. Any characteristic of an element is called a ____.
A. Set
B. Process
C. Variable
D. Census
38. The process of assigning a value of a variable to each element in a data set is called ____.
A. Sampling
B. Measurement
C. Experimental analysis
D. Observational analysis
39. A ____ is a display of individual measurements versus time.
A. Runs plot
B. Statistical analysis
C. Random sample
D. Measurement
40. Statistical _____ refers to using a sample of measurements making generalizations about the important
aspects of a population.
A. Sampling
B. Process
C. Analysis
D. Inference
41. A _____ is a subset of the units in a population.
A. Census
B. Frame
C. Sample
D. Variable
42. A _____ variable can have values that are numbers on the real number line.
A. Qualitative
B. Quantitative
C. Categorical
D. Nominative
43. A sequence of operations that takes inputs and turns them into outputs is a ____.
A. Process
B. Statistical analysis
C. Runs plot
D. Random sampling
44. A(n) _____ variable can have values that indicate into which of several categories of a population it
belongs.
A. Qualitative
B. Quantitative
C. Ratio
D. Interval