Chapter 4

Question 1

operationalization

Answer 1

The process of systematically observing some feature or characteristic of the world and then recording it in the form of a number or category
Must be able to measure theoretical concepts of interest in order to test for suspected cause and effect
Without good measurement, inference is suspect (i.e. theory testing suffers)

Question 2

performance measurement

Answer 2

Use of measurement for administrative purposes or leadership strategy
Focuses on measuring activities outputs, and outcomes of programs, initiatives or even entire organizations

Question 3

construct (trait)

Answer 3

Concept or thing that we seek to measure

Question 4

conceptual clarity

Answer 4

Define characteristics and boundaries of a concept or construct of interest
Know your unti of interest (individuals? Firms? agencies?)
Know your variation of interest (over time? Between units?)
Be precise!

Question 5

conceptualization

Answer 5

Defining carefully and precisely what it is you seek to measure

Question 6

where do conceptualizations come from

Answer 6

Legislations, regulations, policy debates
Insurance coverage/underinsured
Management initiatives
Customer satisfaction
Academic theory
PSM

Question 7

manifest constructs

Answer 7

Things that are factual
More directly observable than others
EX. height and weight of child

Question 8

latent constructs

Answer 8

Things that are not easily measurable
Factors that cannot be observed directly
EX. child’s knowledge of mathematics or language arts, political ideology, self esteem etc.

Question 9

proxies

Answer 9

A proxy measure
EX. eligibility for free school lunch is a proxy measure of the family income of students

Question 10

indicators

Answer 10

Observable measure of an abstract construct
The tradeoff - we get to measure something abstract, usually the cost of increase error

Question 11

scales and indexes

Answer 11

measures composed of multiple indicators
EX. Grade point average
Index formed from grades in all classes
Measures overall academic performance

Question 12

validity

Answer 12

Extent to which your instrument measures the construct of interest
Does what you are measuring map onto the theoretical construct you intended to measure?
Assessment: is your measure of a construct related to other measures (of variables of interest) as predicted by theory?

Question 13

face validity

Answer 13

Based on looking at measure, how well does it get at what we want to measure
(is it valid or face?)

Question 14

content validity

Answer 14

Includes all important dimensions of the construct
Depends on whether it captures the full range of variations of construct
(does an IQ test have items covering all areas of intelligence?)

Question 15

construct validity

Answer 15

Seeing how well our measures correspond with variables that are logically or theoretically related to the underlying construct we purport to measure
(to what extent does this questionnaire actually measure intelligence versus other related variables?)

Question 16

concurrent validity

Answer 16

How well the measure agrees with a current measure of the same concept

Question 17

predictive validity

Answer 17

How well the measure predicts the logical consequences
EX. job satisfaction → quitting (one year)

Question 18

limitations of validity

Answer 18

Validity is not all or nothing
Evidence can be less than completely convincing
There is often no magic test for validity
A measure can be valid for one purpose and not another
Often validity is a matter of subjective judgment

Question 19

random measurement / error noise

Answer 19

Random and average out to 0
Unpredictable and uncontrollable errors
EX. bathroom scale arrow bent

Question 20

Systematic measurement error / bias

Answer 20

Errors that are systematic and on average bend the measure in a particular direction

Question 21

reliability

Answer 21

Extent to which re-application of a measurement method produces identical values for a variable
If you cannot generate the same values for independent or dependent variables successively, confidence in results is diminished

Question 22

bias

Answer 22

Extent to which measure is consistently off of the mark (low or high)
Can still uncover associates between IV and DV
But must be skeptical of size of descriptive and estimated relationship

Question 23

test-retest reliability

Answer 23

Redo and get same results

Question 24

interrater reliability

Answer 24

How similar results are from same researcher when measuring same person or object

Question 25

discrete and continuous numbers

Answer 25

Discrete is full numbers, continuous has decimals
The mathematical qualities of values assigned

Question 26

nominal

Answer 26

Measures or variables in which the numbers refer to categories that have no inherent order to them
Can be arranged in any order
discrete
Cannot be ranked or operated on by any mathematical function
EX. type of car, blood type

Question 27

ordinal

Answer 27

Measures or variables in which the numbers refer to categories that do have an inherent order to them
Numbers convey that order
Discrete
Categories can be ranked
The distance between those ranks is undefined
EX. military rank

Question 28

interval ratio

Answer 28

Numbers the distance between values is the same across all values
Can be discrete or continuous
Constant distance between values
EX. temperature
Interval: arbitrary zero point (temp in c or f)
Ration: zero is meaningful (temp in k)

Question 29

dummy variables

Answer 29

Only have two values, 0 and 1
Represent single unit of something

Question 30

split-half reliability

Answer 30

Divide items randomly into two halves and look at correlation between two halves

Question 31

cronbachs alpha

Answer 31

Averages out variation due to luck of the draw

Question 32

qualitative variables

Answer 32

Numbers refer to actual quantities of something

Question 33

categorical variables

Answer 33

Numbers stand for categories

Question 34

unit of measurement

Answer 34

Prices meaning of numbers that appear in data set

Question 35

simple random sampling

Answer 35

Selecting people or elements from a population in such a way that each individual has an equal chance or probability of selection
Assumed in most basic statistics formulas and statistical software
More complex forms exist - not in this class

Question 36

sampling error

Answer 36

A statistic from a simple random sample is an unbiased estimate for parameter of the population
Proportion unemployed in sample is our guess at proportion unemployed in population
This is why we see things like +/- 3% in surveys
But a random sample results in the estimates that vary somewhat from the true mark, just by luck of the draw

Question 37

parameters

Answer 37

Traits that can be quantified like averages, differences between groups, and relationships among variables

Question 38

central limit theorem

Answer 38

All sampling distributions follow a normal distribution in the limit 9i.e. The larger they get the moral normal and narrow )
Big reason why quantitative research wants lots of observations