Brainscape's Knowledge GenomeTM

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


See full index

2250 Research > Quantitative > Flashcards

Quantitative Flashcards

1
Q

Search Strategies

A
  • Population/situation
  • Intervention/exposure
  • Counter intervention/comparison
  • Outcome
  • Time
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Clues

A
  • Compare
  • Test effectiveness
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Deductive Reasoning

A
  • Theory testing
  • Start general, get specific
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Etic Perspective

A

Outsider

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

Methodology

A
  • Predominant biomedical focus
  • Positivist/post-positivist perspective
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Descriptive

A

Structured observations, survey, or both are used to describe phenomenon, situation, characteristic, group

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

Exploratory

A
  • Gain new insights
  • Discover new ideas
  • Increase knowledge about phenomenon
  • Used when little known about topic
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Casual

A

Experimenting to assess cause and effect

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

Post-Positivism Assumptions

A
  • Reality can be studied and known
  • Objectivity is the ultimate goal
  • Research bias held in check
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Control

A

Measures that the researcher uses to hold conditions of study uniform and avoid basis on the dependent variable or outcome

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

Goals of Control

A
  • Establish specific sample criteria
  • Decrease error & influence of unwanted extraneous variables
  • Increase probability that study findings accurately represent relationship among IVs & DVs
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Internal Validity

A

Changes in the outcome (DV) due to a change in exposure/intervention (IV)

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

Internal Validity Goal

A

Rule out other explanations

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

External Validity

A

Findings generalizable to other populations/settings

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

External Validity Goal

A

Useful beyond participant setting

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

Threats to Internal Validity

A

Names of potential, common types of extraneous variables

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

Selection Bias

A
  • Internal validity threat
  • Characteristics of participants raise possible alternate explanation
  • Small sample size
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

Instrumentation

A
  • Internal validity threat
  • Inter-rater differences
  • Failure of instrument
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

History

A
  • Internal validity threat
  • Event occurs simultaneously with intervention/situation that affects outcome
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

Maturation

A
  • Internal validity threat
  • Natural changes during study affect outcome (DV)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

Testing

A
  • Internal validity threat
  • Act of being tested once affects outcome of next test
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

Mortality (Attrition)

A
  • Internal validity threat
  • Differential loss from groups
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

External Validity Threats

A

Compromise confidence in stating whether the study results are applicable to other groups

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

Selection Effects

A
  • External validity threat
  • Study sample doesn’t represent population of interest
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
Q

Reactivity

A
  • External validity threat
  • Natural reactions to being studied
  • Hawthorne effect
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
26
Q

Hawthorne Effect

A

Participants modify aspect(s) of behaviour in response to awareness of being observed

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

Experimental (RTC) Validity

A
  • Gold standard
  • Controls most validity threats
28
Q

Quasi-Experimental Validity

A

Controls some validity threats

29
Q

Non-Experimental Validity

A

May control some validity threats

30
Q

Descriptive Validity

A

May control some validity threats

31
Q

Experimental Design

A
  • Intervention that is controlled/delivered
  • Experimental (intervention) & control group
  • Random assignment to groups
32
Q

Experimental Design Strengths

A
  • Establish causality/casual direction
  • Control
33
Q

Experimental Design Limitations

A
  • Difficult to implement
  • Generalizability (external validity) low
  • Not ethical for some conditions
34
Q

Quasi-Experimental Design

A
  • Controlled/delivered intervention
  • Experimental group with/without control group
  • No random group assignment
35
Q

Quasi-Experimental Strengths

A
  • Establish causality/casual direction
  • Control (some)
  • Practical (real world adaptability)
  • Increased acceptability (people not always willing to be randomized)
36
Q

Quasi-Experimental Limitations

A
  • Cannot make clear cause/effect statements
  • Generalizability (external validity) low
  • Not ethical for some conditions
37
Q

Sampling

A

Process of selecting subjects to represent population

38
Q

Sampling Planning

A
  • Determine sample characteristics
  • Determine sample size
  • Feasibility/recruitment strategies
  • Ethical considerations
39
Q

Probability Sampling

A
  • Equal & independent probability of selection
  • Rarely used
  • Need to know all elements/people in population
40
Q

Non-Probability Sampling

A
  • Elements chosen non-randomly
  • Most common
41
Q

Simple Random Sampling

A
  • Need a sampling framework
  • Each element has equal & independent probability of selection
  • Use of random number generator etc
42
Q

Systematic Sampling

A
  • Needs sampling frame
  • Uses frame’s order to locate element
  • Faster than simple random
  • May introduce bias (frame arranged to coincide with sampling occurrence)
43
Q

Convenience Sampling

A
  • Non-probability
  • Use elements available at time & place of study
  • Doesn’t require sampling frame
  • Can be fast & efficient
  • May not provide representative sample (atypical of population)
  • If study doesn’t list sample strategy high chance convenience sampling was used
44
Q

Non-Experimental Design

A
  • An effect (outcome/DV) observed in present is linked to potential cause that occurred in past
  • Account of events as they naturally occur
45
Q

Non-Experimental Strengths

A
  • Fewer participants (known outcome)
  • Large number of variables
46
Q

Non-Experimental Limitations

A
  • Difficult to find adequate control group
  • Beware of alternative hypothesis as reason for documented relationship (causality)
  • Validity threats (recall bias, selection bias/effects)
47
Q

Relationship/Difference Studies

A
  • Non-experimental design
  • Explore relationship or differences between variables to provide deeper insight into phenomena
48
Q

Sample Size Justification

A
  • Power calculations
  • Eligibility criteria
49
Q

Type I Error (False Positive)

A
  • Accept study hypothesis
  • Intervention didn’t work
50
Q

Type II Error (False Negative)

A
  • Non-significant result due to too few observations
  • Intervention not effective/no relationship between IV & DV
51
Q

Power

A
  • Ability to detect difference in effect between groups/subjects
  • Many studies may be underpowered
  • Effect size unimportant
  • Power increases with larger sample size
52
Q

Large Power

A
  • More chance to see if an intervention actually works
  • 0.8 = 80% chance to see if intervention works
53
Q

Use of Power Analysis

A

Determine sample size need to minimize risk of type II error (false negative)

54
Q

Effect Size

A

Measure of the magnitude of effect

55
Q

Reliability

A
  • How stable or consistent is the measurement
  • How repeatable is the measurement
56
Q

Validity

A

Is the instrument measuring what it’s supposed to measure

57
Q

High Validity

A
  • High appropriateness of test
  • Difficult to determine
  • Equals high reliability
58
Q

High Reliability

A
  • Test measures what it is supposed to measure
  • No warrantee to be highly valid
  • Test could measure the wrong thing and be invalid
59
Q

Mean

A
  • Average value from data set
  • Sensitive to extreme scores
  • Single number summary for mass of data points
  • Allows for easy comparison between groups
60
Q

Standard Deviation (SD)

A
  • Most common measure of variance
  • How far values stray from mean
61
Q

Small Standard Deviation

A

Scores closer to mean

62
Q

Large Standard Deviation

A

Scores scattered over a wide range round the mean

63
Q

P Value

A
  • Probability that results were due to chance and not based on intervention
  • Range from 0-1
64
Q

Alpha Level

A
  • Critical probability value determined ahead of time
  • Usually set to 0.05 or 0.01
65
Q

P-Value Results

A

Less than alpha value concludes that the difference observed is statistically signifiant

66
Q

P = 0.01

A
  • Statistically significant
  • Results are not due to chance alone but due to a true effect

2250 Research (7 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2025 Bold Learning Solutions. Terms and Conditions