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Introduction to Probability and Statistics
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Chapter 5 / Exercise 22
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Alumin/Shutterstock.com 3 PART Measurement, Data Collection, and Sampling CHAPTER 6 Measurement CHAPTER 7 Primary Data Collection CHAPTER 8 Designing the Data-Gathering Instrument CHAPTER 9 Sampling Methods and Sampling Size CHAPTER 10 Fielding the Data-Gathering Instrument
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Introduction to Probability and Statistics
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Chapter 5 / Exercise 22
Introduction to Probability and Statistics
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99 Learning Objectives Upon completing this chapter, you should understand: What is meant by the measurement process. The differences in nominal, ordinal, interval, and ratio levels of measurements. The concepts of validity and reliability of measurement. What is meant by a measurement scale. How scales are used in business research. CHAPTER Measurement 6 Chapter Outline Introduction The Process of Measurement What Is to Be Measured? Who Is to Be Measured? How to Measure What Needs to Be Measured Assessing Reliability and Validity of Our Measures Measuring Psychological Variables Summary Key Terms Discussion Questions Endnotes KeemMiDo/Shutterstock.com
100 Part 3 Measurement, Data Collection, and Sampling INTRODUCTION In Chapter 1 we described business research as producing the information managers need to make management decisions. In that chapter we also listed numerous examples of how the results of business research can inform management decisions such as in concept and product testing, market segmentation, competitive analysis, customer satisfaction studies, and the like. These, and many other examples of business research studies, illus- trate the need for measurement : “rules for assigning numbers to objects in such a way as to represent quantities of attributes.” 1 Several things we should note about this definition: Gearstd/Shutterstock.com 1. Not all of what researchers do involves measurement. Researchers are interested in generating information, which leads to knowledge, which leads to better decisions. Sometimes that information is in the form of insights from exploratory research studies such as focus groups, in-depth interviews, projective research, and similar methods. For these techniques we are generating information, but we are not assign- ing numbers to objects, so we are not measuring. As we have said before, informa- tion does not have to have numbers attached to it to have value; we are dangerously oversimplifying our analysis when we favor information with numbers over that without, simply because it has the appearance of being hard evidence. 2. The “rules for assigning numbers” will be discussed in greater depth in this chapter, but we should note here that those rules exist so that we can be more scientific in our measures, and can place more confidence in the numbers that those rules help generate (see Figure 1.2). We want to make decisions that are grounded in informa- tion that we believe correctly represent reality. This means the assignment of num- bers should map the empirical nature isomorphically (i.e., on a “one-to-one” basis).

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