Chapter 10: Measurement

Question 1

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| Types of Data</p>

Answer 1

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| Nominal, Ordinal, Interval, Ratio</p>

Question 2

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| Reliability</p>

Answer 2

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A measurement scale that provides consistent results over time and if free from random error</p>

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</p>

Question 3

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| Three Ways to Assess Reliability</p>

Answer 3

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	1. Test-Retest</p>
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	2. Equivalent Form Reliability</p>
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	3. Internal Consistency Reliability</p>

Question 4

Measurement

Answer 4

The process of assigning numbers or labels to obects, persons, states, or events in accordance with specific rules for representing quantities or qualities of attributes.

Question 5

Rule

Answer 5

A guide that tels the researcher what to do

Question 6

Concept

Answer 6

An abstract idea generalized from particular facts

Question 7

Constructs

Answer 7

specific types of concepts that exist at higher levels of abstraction. Examples: Customer satisfaction, brand loyalty, media skepticism, high involvement, etc.

Question 8

Constitutive Definition

Answer 8

Dictionary definition and its relationship to other constructs

Question 9

Media skepticism

Answer 9

The degree to which individuals are skeptical toward the reality presented in the mass media.

Question 10

The Measurement Process

Answer 10

1. Identify the concept of interest
2. Develop a construct
3. a constitutive definition
4. operational definition
5. measurement scales
6. evaluate the reliability and the validity of the scales
7. utilize the scales
8. Research Findings

Question 11

Operational Definition

Answer 11

Defines which observable characteristics will be measured and the process for assigning a value to the concept.

Question 12

Measurement Scale

Answer 12

A set of symbols or numbers such that numbers can be assigned by a rule to the individuals (or their behaviors or attitudes) to whom the scale is applied.

Question 13

Nominal Scales

Answer 13

Uses numerals with out numeric meaning to identify objects, individuals, events or groups.

Question 14

Characteristics of Nominal Data

Answer 14

Determination of equality/inequality. Frequency counts, percentages/modes. Divides data into categories.

Question 15

Ordinal Scales

Answer 15

In addition to identification, the numerals provide information about the relative amount of some characteristic posed by an event, object, etc.

Question 16

Characteristics of Ordinal Data

Answer 16

Median, mean and variance metrics. Ranking.

Question 17

Interval Scales

Answer 17

Possesses all the properties of nominal and ordinal scales plus the intervals between consecutie points are equal.

Question 18

Characteristics of Interval Data

Answer 18

BasiDetermination of equality of intervals, added dimension that the intervals between the data points on scale are equal. Prefer measure of complex concepts/constructs. Uses mean/variance. Ex: Thermometer, Pant size/

Question 19

Ratio Scale

Answer 19

Incorporates all the properties of nominal, ordinal, and interval scales plus it includes an absolute zero point.

Question 20

Characteristics of Ratio Data

Answer 20

Determination of equality of ratios, Used when precision instruments are available, All mathematical calculations are used, examples include age, weight, height, population, income, etc…

Question 21

M = A+E

Answer 21

Measurement = Accuracy + Errors (Random or systematic)

Question 22

Test-Retest Reliability

Answer 22

Obtained by repeating the measurement using the same instrument under as nearly the same conditions as possible.

Question 23

Problems with Test-Retest

Answer 23

• Difficult to locate and gain cooperation from respondents for a second testing
• First measurement may alter the second response
• Environmental or personal factors may change

Question 24

Equivalent Form Reliability

Answer 24

Avoids the test-retest by creating equivalent forms of measurement instrument. Determined by measuring the correlation of the scores on the two instruments.

Question 25

Problems with Equivalent Form Reliability

Answer 25

• Very difficult to create two totally equivalent forms

- If equivalence can be achieved it may not be worth the cost

Question 26

Internal Consistency Reliability

Answer 26

Assesses the ability to produce the similar results using different samples to measure a phenomenon.

Question 27

Equivalence

Answer 27

How much error may be introduced by using different sample of items to measure a phenomenon.

Question 28

Split-Half Technique

Answer 28

Method of assessing the reliability of as scale by dividing the total set of measurement items in half and correlating the results.

Question 29

Validity

Answer 29

Degree to which what the researcher was trying to measure was actually measured.

Question 30

Face Validity

Answer 30

Degree to which a measurement seems to measure what it is supposed to measure.

Question 31

Content Validity

Answer 31

Representativeness, or sampling adequacy, of the content of the measurement instrument.

Question 32

Criterion-Related Validity

Answer 32

Degree to which a measurement instrument can predict a variable that is designated a criterion.

Question 33

Predictive Validity

Answer 33

Degree to which a future level of criterion variable can be forecast by a current measurement scale.

Question 34

Concurrent Validity

Answer 34

Degree to which another variable, measured at the same point in time is as the variable of interest, can be predicted by the measurement instrument.

Question 35

Construct Validity

Answer 35

Degree to which a measurement instrument represents and logically connects, via the underlying theory, the observed phenomenon to the construct.

Question 36

Convergent Validity

Answer 36

Degree of correlation among different measurement instruments that purport to measure the same construct.

Question 37

Discriminant Validity

Answer 37

Measure of the lack of association among constructs that are supposed to be different.