Business Statistics: For Contemporary Decision Making 3rd Canadian Edition by Ken Black Test bank

compare the four different levels of data: nominal, ordinal, interval, and ratio.
Section Reference: 1.2 Variables, Data and Data Measurement
Blooms: Knowledge
AACSB: Analytic
20. With interval-level data, the zero point is a matter of convention and does not mean the
absence of the phenomenon under observation.
Answer: True
Difficulty: Hard
Learning Objective: Explain the difference between variables, measurement, and data, and
compare the four different levels of data: nominal, ordinal, interval, and ratio.
Section Reference: 1.2 Variables, Data and Data Measurement
Blooms: Knowledge
AACSB: Analytic
21. Interval- and ratio-level data are sometimes referred to as quantitative data.
1 - 9  test bank for Business Statistics, Third Canadian Edition
Copyright © 2020 John Wiley & Sons Canada, Ltd. Unauthorized copying, distribution, or transmission of this page is prohibited
Answer: True
Difficulty: Hard
Learning Objective: Explain the difference between variables, measurement, and data, and
compare the four different levels of data: nominal, ordinal, interval, and ratio.
Section Reference: 1.2 Variables, Data and Data Measurement
Blooms: Knowledge
AACSB: Analytic
22. Parametric statistics require that all data used be either interval or nominal.
Answer: False
Difficulty: Hard
Learning Objective: Explain the difference between variables, measurement, and data, and
compare the four different levels of data: nominal, ordinal, interval, and ratio.
Section Reference: 1.2 Variables, Data and Data Measurement
Blooms: Knowledge
AACSB: Analytic
23. Big data refers to a standard set of variables collected from customers, suppliers, and staff.
Ans: False
Difficulty: Easy
Learning Objective: Explain the differences between the four dimensions of big data.
Section Reference: 1.3 Big Data
Blooms: Knowledge
AACSB: Analytic
24. If big data has variety, then it can be said that the data are from several different sources
such as videos, retail scanners, and the internet.
Ans: True
Difficulty: Easy
Learning Objective: Explain the differences between the four dimensions of big data.
Section Reference: 1.3 Big Data
Blooms: Knowledge
AACSB: Analytic
25. Velocity refers to the speed with which data are available to the business for analysis.
Ans: True
Difficulty: Easy
Introduction to Statistics  1 - 10
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Learning Objective: Explain the differences between the four dimensions of big data.
Section Reference: 1.3 Big Data
Blooms: Knowledge
AACSB: Analytic
26. The accuracy, quality and correctness of data is referred to as veracity.
Ans: True
Difficulty: Easy
Learning Objective: Explain the differences between the four dimensions of big data.
Section Reference: 1.3 Big Data
Blooms: Knowledge
AACSB: Analytic
27. The term “garbage in, garbage out” refers to the volume of the data used by a business.
Ans: False
Difficulty: Easy
Learning Objective: Explain the differences between the four dimensions of big data.
Section Reference: 1.3 Big Data
Blooms: Knowledge
AACSB: Analytic
28. Big data can include unstructured data such as writings and photographs.
Ans: True
Difficulty: Easy
Learning Objective: Explain the differences between the four dimensions of big data.
Section Reference: 1.3 Big Data
Blooms: Knowledge
AACSB: Analytic
29. Big data should encompass all four characteristics of variety, velocity, virtuous, and volume.
Ans: False
Difficulty: Easy
Learning Objective: Explain the differences between the four dimensions of big data.
Section Reference: 1.3 Big Data
Blooms: Knowledge
AACSB: Analytic
30. Descriptive statistics focuses on what has happened or is happening within the business.
1 - 11  test bank for Business Statistics, Third Canadian Edition
Copyright © 2020 John Wiley & Sons Canada, Ltd. Unauthorized copying, distribution, or transmission of this page is prohibited
Ans: True
Difficulty: Easy
Learning Objective: Compare and contrast the three categories of business analytics.
Section Reference: 1.4 Business Analytics
Blooms: Knowledge
AACSB: Analytic
31. Prescriptive analytics is the second step in big data analysis, following descriptive statistics.
Ans: False
Difficulty: Easy
Learning Objective: Compare and contrast the three categories of business analytics.
Section Reference: 1.4 Business Analytics
Blooms: Knowledge
AACSB: Analytic
32. Prescriptive analytics is optimal for taking risk and uncertainty into account by looking at the