Chapter 1 Introduction to Quantitative Analysis

1) Interviews, statistical sampling, and company reports provide input data for quantitative analysis models.

2) In the early 1900s, Henry Ford pioneered the principles of the scientific approach to management.

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3) Managers do not need to be familiar with the limitations, assumptions, and/or specific applicability of the quantitative analysis technique to use it for accurate decision making.

4) During World War II, many new scientific and quantitative techniques were developed to assist the military, and these developments were so successful that many companies started using similar techniques in managerial decision making and planning after the war.

5) Business Analytics is a data-driven approach to decision making that allows companies to make better decisions.

6) Descriptive Analytics is aimed at forecasting future outcomes based on patterns in the past data.

7) When a problem is difficult to quantify, it may be necessary to develop unspecific objectives.

8) The Quantitative Analysis Approach consists of six steps.

9) A mathematical model shows the relationship between quantifiable and non-quantifiable information.

10) Decision variables may also be called parameters.

11) Model variables can be controllable or uncontrollable.

12) A series of steps or procedures that are repeated is known as an algorithm.

13) A model is a representation of a situation.

14) A parameter is a measurable quantity that may vary or is subject to change.

15) Trying various approaches and picking the one resulting in the best decision is called incomplete enumeration.

16) All problems can be solved by considering only the quantitative issues.

17) A profit equation is an example of a schematic model.

18) Testing the data and model should be done before the results have been analyzed.

19) Sensitivity analysis helps us estimate the effect of known and unknown errors in our model.

20) Models can help us analyze a problem and sell a decision to those who must implement it.

21) A sensitivity analysis allows a manager to answer the “what if” questions.

22) One problem in using a quantitative model is that the necessary data may be unavailable.

23) Management support and user involvement are not essential in the successful implementation of quantitative analysis projects.

24) Which of the following terms is interchangeable with quantitative analysis?

A) management science

B) economics

C) financial analysis

D) statistics

E) None of the above

25) Operations Research is known as

A) the science of numerical analysis.

B) the science of sensitivity analysis.

C) the science of better.

D) the science of modeling.

E) None of the above

26) Who is credited with pioneering the principles of the scientific approach to management?

A) Adam Smith

B) Henri Fayol

C) John R. Locke

D) Frederick W. Taylor

E) Charles Babbage

27) Which of the following techniques involves the study and consolidation of historical data for a business and an industry?

A) descriptive analytics

B) prescriptive analytics

C) predictive analytics

D) management science

E) operations research

28) Which of the following techniques involves the use of optimization methods to provide new and better ways to operate based on specific business objectives?

A) descriptive analytics

B) prescriptive analytics

C) predictive analytics

D) quantitative analysis

E) qualitative analysis

29) A(n) ________ is a representation of reality or a real-life situation.

A) objective

B) model

C) analysis

D) algorithm

E) None of the above

30) A measurable quantity that may vary, or is subject to change, and can be controlled is known as a(n)

A) decision variable.

B) algorithm.

C) parameter.

D) solution.

E) None of the above