Ch13: MEASUREMENT AND SCALING CONCEPTS Flashcards
measurement
The process of describing some property of a phenomenon of interest, usually by assigning numbers in a reliable and valid way
What Do I Measure?
The decision statement, corresponding research questions, and research hypotheses can be used to decide what concepts need to be measured in a given project.
Concepts
What Do I Measure?
A researcher has to know what to measure before knowing how to measure something. The problem definition process should suggest the concepts that must be measured. A concept can be thought of as a generalized idea that represents something of meaning. Concepts such as age, sex, education, and number of children are relatively concrete properties
operationalization
Researchers measure concepts through a process known as operationalization
The process of identifying scales that correspond to variance in a concept to be involved in a research process.
Scales
Scales, just as a scale you may use to check your weight, provide a range of values that correspond to different values in the concept being measured
A device providing a range of values that correspond to different values in a concept being measured.
correspondence rules
Indicate the way that a certain value on a scale corresponds to some true value of a concept.
In other words, scales provide correspondence rules that indicate that a certain value on a scale corresponds to some true value of a concept. Hopefully, they do this in a truthful way.
construct
A construct is a term used for concepts that are measured with multiple variables. For instance, when a business researcher wishes to measure the customer orientation of a salesperson, several variables like these may be used, each captured on a 1–5 scale:
- I offer the product that is best suited to a customer’s problem.
- A good employee has to have the customer’s best interests in mind.
- I try to find out what kind of products will be most helpful to a customer.
Levels of Scale Measurement
Nominal Scale Ordinal Scale Interval Scale Ratio Scale Mathematical and Statistical Analysis of Scales
Levels of Scale Measurement
Nominal Scale
Nominal scales represent the most elementary level of measurement. A nominal scale assigns a value to an object for identification or classification purposes only.
Example: Student ID Yes – No Male – Female Buy – Did Not Buy East region Central region West region
Levels of Scale Measurement
Ordinal Scale
Ordinal scales allow things to be arranged in order based on how much of some concept they possess. In other words, an ordinal scale is a ranking scale. In fact, we often use the term rank order to describe an ordinal scale. When class rank for high school students is determined, we have used an ordinal scale.
Example: Student class rank Counting Please rank your three favorite movies. Choose from the following • Dissatisfied • Range • Satisfied • Very satisfied • Delighted Indicate your level of education: • Some high school • High school diploma • Some college • College degree • Graduate degree
Levels of Scale Measurement
Interval Scale
Interval scales have both nominal and ordinal properties, but they also capture information about differences in quantities of a concept.
Example: Student grade point average (GPA) Temperature (Celsius and Fahrenheit) Points given on an essay question 100-point job performance rating provided by supervisor
Levels of Scale Measurement
Ratio Scale
Ratio scales represent the highest form of measurement in that they have all the properties of interval scales with the additional attribute of representing absolute quantities. Interval scales possess only relative meaning, whereas ratio scales represent absolute meaning. In other words, ratio scales provide iconic measurement.
Example: Amount spent on last purchase Salesperson sales volume Number of stores visited on a shopping trip Annual family income Time spent viewing a Web page
Levels of Scale Measurement
Mathematical and Statistical Analysis of Scales
While it is true that mathematical operations can be performed with numbers from nominal scales, the result may not have a great deal of meaning. For instance, a school district may perform mathematical operations on the nominal school bus numbers. With this, they may find that the average school bus number is 77.7 with a standard deviation of 20.5. Will this help them use the buses more efficiently or better assign bus routes? Probably not. Can a professor judge the quality of her classes by the average ID number? While it could be calculated, the result is meaningless. Thus, although you can put numbers into formulas and perform calculations with almost
any numbers, the researcher has to know the meaning behind the numbers before meaningful conclusions can be drawn.
Mathematical and Statistical Analysis of Scales
DISCRETE MEASURES
Discrete measures are those that take on only one of a finite number of values. A discrete scale is most often used to represent a classification variable.
Common discrete scales include any yes-or-no response, matching, color choices, or practically any scale that involves selecting from among a small number of categories. Thus, when someone is asked to choose from the following responses
• Disagree
• Neutral
• Agree
the result is a discrete value that can be coded 1, 2, or 3, respectively. This is also an ordinal scale to the extent that it represents an ordered arrangement of agreement. Nominal and ordinal scales are discrete measures.
Mathematical and Statistical Analysis of Scales
CONTINUOUS MEASURES
Continuous measures are those assigning values anywhere along some scale range in a place that corresponds to the intensity of some concept. Ratio measures are continuous measures. Thus, when Griff measures sales for each salesperson using the dollar amount sold, he is assigning a continuous measure.
Strongly Disagree Disagree Neutral Agree Strongly Agree
I enjoy participating
in online auctions
1 2 34 5.
This is a discrete scale because only the values 1, 2, 3, 4, or 5 can be assigned. Furthermore, it is an ordinal scale because it only orders based on agreement. We really have no way of knowing that the difference in agreement of somebody marking a 5 instead of a 4 is the same as the difference in agreement of somebody marking a 2 instead of a 1. Therefore, the mean is not an appropriate way of stating central tendency and, technically, we really shouldn’t use many common statistics on these responses.
