Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

KIN 209 > Lecture 6 > Flashcards

Lecture 6 Flashcards

1
Q

Within a postpositivist worldview, quantitative strategies are
used to answer research questions and test hypotheses related to:

A
  • determining associations
  • comparing groups
  • developing and testing measures
  • theory verification
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

5 step process of quantitative design process:

A
  • determining basic questions to be answered
  • determining study participants
  • selecting methods needed to answer questions
  • selecting analysis tools
  • understand and interpret results
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

When using hypotheses, it is important that they are developed with _____ in mind.

A

theory

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

The research question is key as it guides the ____ selected.

A

method

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

An advantage of quantitative research is one can use _____ groups (_____) to potentially make ______ to the _____
population

A
  • smaller
  • sample
  • inferences
  • larger
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Population:

A

An entire group or aggregate of people or elements having one or more common characteristic

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Sample frame:

A

The group of accessible people that can be connected with about the study

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Sample:

A

A sub-group of the population that can be managed by the researcher but will represent the population

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Sampling:

A

The process a researcher uses to obtain a sample

from the target population

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

2 types of sampling:

A
  • probability

- nonprobability

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

In probability sampling, samples are selected using ____ _____ ensuring that…

A
  • random processes

- every unit in the population has an equal probability of being selected

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

In probability sampling, the probability of selecting each participant or element is _____.

A

known

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

In probability sampling, estimating sampling error is _____.

A

possible

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

In non-probability sampling, how are samples selected?

A

not selected at random

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

In non-probability sampling, the probability of selecting each participant or element is ______.

A

unknown

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

In non-probability sampling, it is difficult to say if your sample is… and in turn difficult to…

A
  • representative of population

- generalize findings

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Non-probability sampling is ____ expensive and ____ complicated.

A
  • less

- less

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

4 types of probability sampling:

A
  • simple random sampling
  • stratified random sampling
  • systematic sampling
  • cluster sampling
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

Simple random sampling:

A
  • every individual has equal opportunity of being selected

- selection of one member does not affect the chances of another member being chosen

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

Stratified random sampling:

A
  • dividing population elements into subgroups (STRATA) the randomly sample from each
  • ensures representation from each strata
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

Systematic sampling:

A
  • sampling units are selected in series according to some preset criteria or sequence
  • selection of the 1st element is random, but after this selection is not independent (ex. select every 10th entry)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

Cluster sampling:

A
  • participants are randomly selected from a natural occurring group or unit in a population
  • researcher specifies the cluster, which becomes the sampling unit
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

When to use simple random sampling:

A

anytime

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

When to use stratified random sampling:

A

when concerned about under representing subgroups

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
Q

When to use systematic sampling:

A

when you want to sample every kth element in a ordered set

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
26
Q

When to use cluster sampling:

A

when organizing geographically makes sense

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
27
Q

Advantage of simple random sampling:

A
  • simple to implement

- easy to expalin

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
28
Q

Advantage of stratified random sampling:

A

allows oversample of minority groups to ensure subgroup analysis

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
29
Q

Advantage of systematic sampling:

A

does not require that you count through all of the elements in the list to find the ones randomly selected

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
30
Q

Advantage of cluster sampling:

A

is more efficient than other methods when sampling across geographically dispersed areas

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
31
Q

Disadvantage of simple random sampling:

A

requires a sample list to select from

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
32
Q

Disadvantage of stratified random sampling:

A

requires a sample list to select from

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
33
Q

Disadvantage of systematic sampling:

A

if the order of the elements is nonrandom, there could be systematic bias

34
Q

Disadvantage of cluster sampling:

A

is usually not used alone, combined with other methods

35
Q

3 types of nonprobability sampling:

A
  • purposive sampling
  • convenience sampling
  • snowball sampling
36
Q

Purposive sampling:

A
  • participants purposefully selected because they have specific characteristics the researcher is interested in
  • not randomly selected = limited generalizability
  • commonly used with very small sample sizes
  • common in qualitative research
37
Q

Convenience sampling:

A

selecting research participants on the basis of being available, accessible, and convenient to the researcher

38
Q

Snowball sampling:

A

enrolled participants nominate or recruit potential participants who may meet the eligibility criteria

39
Q

When to use purposive sampling:

A

when you want to examine specific characteristics or experiences

40
Q

When to use convenience sampling:

A

anytime

41
Q

When to use snowball sampling:

A

hard to reach populations

42
Q

Advantage of purposive sampling:

A

easily understood, implement, and explain

43
Q

Advantage of convenience sampling:

A

easy to do

44
Q

Advantage of snowball sampling:

A

can be used with no sampling frame

45
Q

Disadvantage of purposive sampling:

A

limited external validity, likely to be biased

46
Q

Disadvantage of convenience sampling:

A

very weak external validity, likely to be biased

47
Q

Disadvantage of snowball sampling:

A

low external validity

48
Q

2 questions when selecting methods needed in quantitative design process:

A
  • how many measurements are being used?

- what types of measures or observations are being used?

49
Q

Selecting methods needed includes identifying:

A
  • variables
  • measures
  • design
50
Q

Variable:

A

an attribute or a characteristic that may vary over time or across cases

51
Q

Types of variables:

A
  • independent
  • dependent
  • mediator
  • moderating
  • control
  • confounding
52
Q

Dependent variable (DV):

A
  • The variable that is being
    affected
  • it is the outcome being assessed as a result of the
    independent variable(s) and is the main focus of the study
53
Q

Independent variable (IV):

A

the variable that is being manipulated (also called treatment variable)

54
Q

Mediator variable:

A

A variable that is proposed to at least partially explain the relationship between an IV and the DV

55
Q

Moderating variable:

A

A variable that affect the relationship between two other variables (predictor and outcome)

56
Q

Control variable:

A

A variable that could influence the outcome or results of the study . . . not the main focus of the study

57
Q

Confounding variable:

A

An unmeasured variable that is controlled for in the study. It could be the variable could not be measured

58
Q

4 types of measures:

A
  • observational
  • self-report measures
  • objective
  • estimates
59
Q

Observational measures:

A

recorded by individual observing an action

60
Q

Self-report measures:

A

an individual reports their own behaviour

61
Q

Objective measures:

A

taken by instruments or other calibrated devices

62
Q

Estimate measures:

A

subject matter experts provide best guesses

63
Q

Validity asks…

A

does the measure do what i is supposed to do?

64
Q

Reliability asks…

A

does the measure lead to consistent results?

65
Q

3 common types of validity as it relates to measurements:

A
  • construct
  • content
  • criterion
66
Q

Construct validity:

A

how one translates the idea or construct into something real or concrete

67
Q

Content validity:

A

a check of the operationalization against the relevant content domain of the construct

68
Q

Criterion validity:

A

the validation of a measure based on its relationship to another independent measure as predicted by your theory of how the measures should behave

69
Q

Reliability:

A

the repeatability or consistency of a test (or tester) or instrument

70
Q

Reliability is important because any change in scores should reflect a true indication of one’s _____ and not….

A
  • ability
  • change over a short period of time
  • depend on who is administering the test
71
Q

A valid measurement is _____, but having ______ measurements does not always mean they are valid.

A
  • reliable

- reliable

72
Q

4 general classes of reliability estimates:

A
  • inter-rater or inter-observer reliability
  • test-retest reliability
  • parallel-forms reliability
  • internal consistency reliability
73
Q

Inter-rater or inter-observer reliability:

A

assess the degree to which different raters/observers give consistent estimates of the same phenomenon

74
Q

Test-retest reliability:

A

assess the consistency of a measure from one time to another

75
Q

Parallel-forms reliability:

A

assess the consistency of the results of 2 tests constructed in the same way from the same content domain

76
Q

Internal consistency reliability:

A

consistency of results across items within a test

77
Q

Shooting-target metaphor: reliable not valid

A

you are hitting the target consistently but you are missing the centre of the target (it is consistent but not right)

78
Q

Shooting-target metaphor: valid not reliable

A
  • hits are randomly spread across the target
  • seldom hit bulls-eye but on average are getting the right answer for the group (target)
  • group estimate is valid, but inconsistent
79
Q

Shooting-target metaphor: neither reliable nor valid

A
  • hits are spread across the top part of the target but are consistently missing the bulls eye
  • it is consistent and is not right
80
Q

Shooting-target metaphor: both reliable and valid

A
  • consistently hitting the centre of the target

- both consistent and correct

KIN 209 (21 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions