chp.10

Question 1

4 steps from data collection to sumamry:

Answer 1

Collect the data

Deal with data errors/omissions

Reduce data to manageable size

Develop summaries

Question 2

what is data?

Answer 2

collective units of information from a subject or case
measured by a data collector following consistent
procedures

raw and unprocessed

Question 3

what does consistency make data?

Answer 3

verifiable, but not necessarily truthful

Question 4

2 types of data

Answer 4

primary
secondary

Question 5

primary data

Answer 5

data the research collects to address the specific
problem at hand

Question 6

secondary data

Answer 6

originally collected to address a problem other than the
one which require the manager’s attention at the
moment

Question 7

6 dimensions of data quality

Answer 7

accuracy
consistency
validity
completeness
uniqueness
integrity

Question 8

accuracy

Answer 8

the level to which data represents the real-world scenario and confirms with a verifiable source

Question 9

consistency

Answer 9

represents if the same information stored and used at multiple instances matches.
Expressed as the percent of matched values across various records.

Question 10

validity

Answer 10

signifies that the value attributes are available for aligning with the specific domain or requirement.

Question 11

completeness

Answer 11

measures if the data is sufficient to deliver meaningful inferences and decisions

Question 12

uniqueness

Answer 12

indicates if it is a single recorded instance in the data set used. Ensures no duplication or
overlaps.

Question 13

integrity

Answer 13

indicates that the attributes are maintained correctly, even as data gets stored and used in
diverse systems. Ensures that all enterprise data can be traced and connected.

Question 14

measurement

Answer 14

assigning numbers to empirical events, objects or properties, or activities in compliance with a set of rules.

Question 15

what’s a mapping rule

Answer 15

scheme for assigning numbers to aspects of an empirical event

Question 16

4 most used classifications of measurement

Answer 16

nominal - male or female
ordinal - low/middle/high income
interval - 13 degrees
ratio - defined 0 point eg lbs or $

Question 17

4 characteristics of mapping rules

Answer 17

classification
order
distance
origin

Question 18

classification

Answer 18

numbers are used to group or sort responses.

Question 19

order

Answer 19

numbers are ordered. One number is greater than, less than, or equal to another number.

Question 20

distance

Answer 20

differences between numbers can be measured.

Question 21

origin

Answer 21

the number series has a unique origin indicated by the number zero.

Question 22

:)

Answer 22

:)

Question 23

nominal

Answer 23

Mutually Exclusive

Collectively Exhaustive
Categories

Classification Only

Question 24

ordinal

Answer 24

Nominal Scale
Characteristics

+ Order

Conforms to logical
postulate (> or <)

Question 25

interval

Answer 25

Ordinal Scale Characteristics Equality of interval Equality of distance between numbers

Question 26

ratio

Answer 26

Interval Scale Characteristics Absolute Zero

Question 27

Recoding

Answer 27

Adjust variable after data collection Apply new mapping rules Only REDUCE variable power Less powerful statistical analysis

Question 28

4 sources of error

Answer 28

participant situation measurer instrument

Question 29

participant error

Answer 29

Opinion differences that affect measurement come from relatively stable characteristics of the participant.

Question 30

situation error

Answer 30

Any condition that places a strain on the interview or measurement session.

Question 31

measurer error

Answer 31

The interviewer can distort responses by rewording, paraphrasing, or reordering questions. Stereotypes in appearance and action. Careless mechanical processing.

Question 32

instrument error

Answer 32

A defective instrument can cause distortion by being too confusing and ambiguous and not all-encompassing.

Question 33

3 characteristics of good measurement

Answer 33

valid reliable practical

Question 34

validity

Answer 34

the extent to which a test measures what we wish to measure.

Question 35

reliability

Answer 35

refers to the accuracy and precision of a measurement procedure.

Question 36

practicality

Answer 36

concerned with a wide range of factors of economy, convenience, and interpretability.

Question 37

what does this tell us

Answer 37

WITHOUT RELIABILITY YOU CANNOT HAVE VALIDITY… you can be reliable and not valid - You can consistently measure the wrong thing

Question 38

A measure is reliable to the degree that it...

Answer 38

...supplies consistent results

Question 39

Reliable instruments are...

Answer 39

robust and work well under different times and different conditions

Question 40

The distinction of time and condition is the basis for three perspectives on reliability...

Answer 40

stability equivalence internal consistency

Question 41

measures: stability

Answer 41

secure consistent results with repeated measurements of the same person with the same instrument.

Question 42

how to test for stability

Answer 42

test-retest, a correlation will tell you how stable something is

Question 43

Internal consistency is a characteristic of an instrument...

Answer 43

...in which the items are homogeneous.

Question 44

equivalence is concerned with...

Answer 44

...variations at one point in time among observers and samples of items.

Question 45

equivalence can be seen if...

Answer 45

...we get a few observers to score or observe one event, and see how similar they all are

Question 46

scientific requirements

Answer 46

measurements to be reliable and valid

Question 47

operational requirements

Answer 47

measurements to be practical

Question 48

practicality means we consider: (3 things)

Answer 48

economy convenience interpretability

Question 49

how does a measuring device pass the convenience test?

Answer 49

if it's easy to administer

Question 50

why is interprebility important?

Answer 50

for when people other than the test designer want to assess results/data/info