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What is a Number?
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What is a number? Names and symbols are arbitrary.
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What is a number? Names and symbols are arbitrary. Four…. IV …. 4….
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What is a number? Names and symbols are arbitrary.
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Numbers that are not numbers…. 0 http://en.wikipedia.org/wiki/0_%28number%29
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Numbers that are not numbers… Some make the world go around. e
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What is a number? Names and symbols are arbitrary. Measurement: “Rules for assigning numbers to objects (or concepts) to represent quantities of attributes.”
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What is a number? Names and symbols are arbitrary. Measurement:
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What is a number? Names and symbols are arbitrary. But to be a true number scale the symbols must follow some logical and systematic arrangement.
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What is a number? Names and symbols are arbitrary. Measurement: “Standardized process of assigning symbols to objects according to certain prespecified and nondegenerating rules.”
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Is it possible to have an IQ of 160? But what does it mean? 160 Degenerating!
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What is a number? Names and symbols are arbitrary. Measurement:
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What is a number? Names and symbols are arbitrary. Measurement: “An object is never measured… only the object’s attributes.”
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Object characteristics. are measured, not objects,
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What is a number? Scales: “A scale is the continuum upon which measurements are located.”
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Zero degrees centigrade….
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So then what is this…..
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What is a number? Scales: Likert Scale Is a statement (not a question) followed by five categories of agreement.
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What is a number? Scales: Likert Scale Ice cream is good for breakfast. 1. Strongly disagree 2. Disagree 3. Neither agree nor disagree 4. Agree 5. Strongly agree
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What is a number? Scales: Likert Scale
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What is a number? Scales: Likert Scale
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What is a number? Scales: Likert
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What is a number? Scales:
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What is a number? Scales: Semantic scales: Typically: Opposite adjectives separated by 7 selection points.
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What is a number? Scales:
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Semantic scales:
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Semantic scales:
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Hybrid Scales:
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But complex concepts in business may not be easily measured.
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What is a number? So….. Harvard professor S.S. Stevens created numerical scales to measure difficult concepts.
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S. S. Stevens 1906 - 1973
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Steven’s original paper in Science, 103(2684), June 7, 1946.
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Steven’s Scales: Ratio
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Steven’s Scales: 1. Nominal Scales
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Steven’s Scales: 1. Nominal Scales a. Name
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Steven’s Scales: 1. Nominal Scales a. Name b. Classify
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Steven’s Scales: 1. Nominal Scales a. Name b. Classify c. Categorize
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Steven’s Scales: 1. Nominal Scales a. Name b. Classify c. Categorize
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Steven’s Scales: 1. Nominal Scales 2. Ordinal Scales
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Steven’s Scales: 1. Nominal Scales 2. Ordinal Scales Does everything a nominal scales does. Ranks objects or concepts by some characteristic. http://www.usatoday.com/sports/ncaab/sagarin/
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Steven’s Scales: 1. Nominal Scales 2. Ordinal Scales 3. Interval scales
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Steven’s Scales: 1. Nominal Scales 2. Ordinal Scales 3. Interval scales Does everything an ordinal scale does. Interval is now meaningful.
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Steven’s Scales: 1. Nominal Scales 2. Ordinal Scales 3. Interval scales 4. Ratio scales
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Steven’s Scales: 1. Nominal Scales 2. Ordinal Scales 3. Interval scales 4. Ratio scales Has all the characteristics of all other scales, but it also has meaningful ratios. It has a true zero.
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http://www.fao.org/docrep/W3241E/w3241e04.htm Good source:
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Steven’s Scales: 1. Nominal Scales 2. Ordinal Scales X = f(x) 3. Interval scalesX = kx + c 4. Ratio scalesX = kx
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Which scale to use? 1. Amount of information needed
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Which scale to use? 1. Amount of information needed Each higher scale carries more information than the one before it.
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Which scale to use? 1. Amount of information needed 2. Characteristics of stimulus or concept
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Which scale to use? 1. Amount of information needed 2. Characteristics of stimulus or concept 3. Application context
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Which scale to use? 1. Amount of information needed 2. Characteristics of stimulus or concept 3. Application context 4. Capacity of scale
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Which scale to use? 1. Amount of information needed 2. Characteristics of stimulus or concept 3. Application context 4. Capacity of scale 5. Post-measurement analysis
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Which scale to use? 1. Amount of information needed 2. Characteristics of stimulus or concept 3. Application context 4. Capacity of scale 5. Post-measurement analysis Statistics are designed for specific types of scales. Using the wrong scale will give answers that are nonsense.
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Measurement characteristics:
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Y = x(true) + x(sy-error) + x(random)
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Measurement characteristics: Y = x(true) + x(sy-error) + x(random) Systematic error can be eliminated.
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Measurement characteristics: Y = x(true) + x(sy-error) + x(random) Random error cannot be eliminated.
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Measurement characteristics: Y = x(true) + x(sy-error) + x(random) If a sample is taken to estimate an answer: another form of error is added……
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Measurement characteristics: This is called a Sampling Error Y = x(true) + x(sy-error) + x(random) + x(sampling error)
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You and a friend (in the same class) take the same exam at the same time and get different grades.
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WHY?
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Take a piece of paper… write down five different reasons why these two friends taking the same class would get different grades... What then did the grade actually measure? Write down a definition of a “grade.” If you suggested that a “grade” is a measurement of what a student knows, how many “grades” would you suggest needs to be taken to be confident that the student knows what the grades indicate that they know?
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Measurement characteristics: Validity Before validity can be established, it is necessary to show that measurements have reliability. A measurement can be reliable without being valid, but it cannot be judged to be valid without reliability.
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Measurement characteristics: Reliability
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Measurement characteristics: Reliability 1. Stability
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Measurement characteristics: Reliability 1. Stability a.Test-retest b. Equivalent forms
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Measurement characteristics: Reliability 1. Stability a.Test-retest b. Equivalent forms 2. Equivalence
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Measurement characteristics: Reliability 1. Stability a.Ttest-retest b. Equivalent forms 2. Equivalence a. Kuder-Richardson b. Cronbach’s Alpha
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Measurement characteristics: Reliability 1. Stability a.Test-retest b. Equivalent forms 2. Equivalence a. Kuder-Richardson b. Cronbach’s Alpha Lee Cronbach
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Measurement characteristics: Reliability 1. Stability a.Test-retest b. Equivalent forms 2. Equivalence a. Kuder-Richardson b. Cronbach’s Alpha Learn, Effective, & Like the instructor
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Measurement characteristics: Reliability 1. Stability a.Test-retest b. Equivalent forms 2. Equivalence a. Kuder-Richardson b. Cronbach’s Alpha 3. Inter-rater Consistency a. Krippendorff’s Alpha Klaus Krippendorff 1932 -
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Measurement characteristics: If a measurement is reliable, it may be valid: But there are many ways that a measurement could be valid or invalid.
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Measurement characteristics: Validity 1. Face validity
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Measurement characteristics: Validity 1. Face 2. Content
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Measurement characteristics: Validity 1. Face 2. Content 3. Criteria
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Measurement characteristics: Validity 1. Face 2. Content 3. Criteria a. Concurrent b. Predictive
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Measurement characteristics: Validity 1. Face 2. Content 3. Criteria a. Concurrent b. Predictive 4. Construct
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Measurement characteristics: Validity 1. Face 2. Content 3. Criteria a. Concurrent b. Predictive 4. Construct
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Measurement characteristics: Validity 1. Face 2. Content 3. Criteria a. Concurrent b. Predictive 4. Construct a. Convergent
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Measurement characteristics: Validity 1. Face 2. Content 3. Criteria a. Concurrent b. Predictive 4. Construct a. Convergent b. Divergent
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Measurement characteristics: Validity 1. Face 2. Content 3. Criteria a. Concurrent b. Predictive 4. Construct a. Convergent b. Divergent c. Discriminant
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Measurement characteristics: Validity 1. Face 2. Content 3. Criteria a. Concurrent b. Predictive 4. Construct a. Convergent b. Divergent c. Discriminant d. Nomological
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Measurement characteristics: Validity 1. Face 2. Content 3. Criteria a. Concurrent b. Predictive 4. Construct 5. Utilitarian (?) A measurement may satisfy a utilitarian goal independently of any validity of the actual measurement.
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