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Research Flashcards

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1
Q

Normative analysis

A

prescriptive, based in reason and logic

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2
Q

Empirical analysis

A

descriptive / explanatory, based on observation and measurement

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3
Q

Scientific approach

A

an understanding of knowledge (epistemology) and way of obtaining knowledge (methodology)

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4
Q

Positivism

A

there is an objective reality

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5
Q

Interpretivism

A

reality changes with perspective and is decided by the individual

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6
Q

Core beliefs of scientific approach

A
  • Empiricism: knowledge is derived from real world observation, not theoretical deduction
  • Determinism: everything has a cause that we can find
  • Objectivity: science should accurately represent reality
  • Replication: science is cumulative, so we need to repeat research to make sure it’s correct
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7
Q

Intersubjectivity

A

multiple studies should demonstrate similar findings

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8
Q

Components of a research report

A
  1. Abstract/executive summary
  2. Introduction
  3. Research design
  4. Presentation of findings
  5. Discussion
  6. Conclusions
  7. References
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9
Q

Null findings

A

research that results in no proven connection between 2 concpets

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10
Q

Replicable

A

showing you research so others can replicate it to prove your hypothesis

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11
Q

Transmissible

A

using research that is easy to understand

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12
Q

Informed consent

A

research participants need to fully understand the extent to which they will participation and the nature of the project

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13
Q

Systematic errors

A

getting the same wrong answer after multiple attempts

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14
Q

Random errors

A

getting different answers each time you attempt

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15
Q

Levels of measurement (NOIR)

A
  • Nominal: only names and categories
  • Ordinal: ordered information
  • Interval / Ratio: exact numbers
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16
Q

Applied research

A

research done to solve a real world problem

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17
Q

Basic research

A

research done for the sake of understanding new ideas

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18
Q

Measurement errors

A

gap in between you expected result and the actual result

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19
Q

Positive correlation

A

both variables move in the same direction (up or down)

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20
Q

Negative correlation

A

variables move in opposite directions

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21
Q

Causation

A

one concept happens because of another concept

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22
Q

Correlation

A

2 concepts move similarly, but this may not be because of each other

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23
Q

Independent variable

A

the variable that isn’t changed by the other (cause)

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24
Q

Dependent variable

A

the variable that changes based on the other one (effect)

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25
Q

Types of random sampling

A
  • Simple: draw from a group
  • Systemic: creating an algorithm to draw from a group
  • Proportionate: random selection based on the percentages in the population
  • Disproportionate: weighted random selection to over-represent certain groups
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26
Q

Types of non-random sampling

A
  • Convenience / Accidental: sampling the first people you can find
  • Volunteer: people select to be a part of the sample
  • Purposive / Judgemental: manually creating a sample from personal judgement and knowledge
  • Snowball: starting with a small group who then ask others like them
  • Quota: selecting people to fill a requested list
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27
Q

Sampling error

A

difference in sample statistic and population parameter

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28
Q

Margin of error / confidence interval

A

how close the sample is to the population (as represented by a % range)

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29
Q

Document analysis

A

gathering key facts and basic level information from documents (names, dates, times, numbers)

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30
Q

Text analysis

A

systematic study of content, form, and substance of a text

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31
Q

Discourse analysis

A

what the text says about society, meaning, and interactions

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32
Q

Content analysis

A

message of the text, frequency of terms, length of text

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33
Q

Structural content analysis

A

physical measurements of the content (pictures, titles)

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34
Q

Substantive content analysis

A

what is being said or written (idealogical leanings, coverage bias)

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35
Q

Manifest content

A

visible surface content

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36
Q

Latent content

A

underlying meaning of the content

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37
Q

Codebook

A

rules of the analysis (what words you are looking for, what part of the content)

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38
Q

Intercoder reliabilty

A

multiple people reading or watching the same content and getting the same result

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39
Q

Interviewer effect

A

the impact the interviewer’s presence has on the interviewee and the information shared

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40
Q

Observation research

A

observing behaviour in it’s natural setting as it occurs

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41
Q

Participant observation

A

being a part of the group you are studying

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42
Q

Obtrusive participant observation

A

the group knows they are being studied

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43
Q

Unobtrusive participant observation

A

the group does not know they are being studied

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44
Q

Covert participant observation

A

undercover observation of a group (illegal)

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45
Q

True participant observation

A

researching a group you already belong to

46
Q

Participant observer

A

identifying yourself to the group you will be studying

47
Q

Complete observer

A

observing the behaviour of a group from outside the group

48
Q

Reactivity

A

the researcher’s impact upon the group they are studying and the information shared

49
Q

Data saturation

A

no new information is gained from new interviews and studies

50
Q

Interview framework

A

guidelines of what information you want to ask in the interview

51
Q

Hawthorne effect

A

people will change their answers when they know they are being studied (social desirability)

52
Q

Focus group

A

small group of similar people with the purpose of gaining new and specialized information

53
Q

Secondary data

A

data collected by another researcher that you are allowed to use

54
Q

Closed-ended questions

A

participants have to choose from a preset group of answers

55
Q

Open-ended questions

A

participants can answer in any way they want

56
Q

Exhaustive

A

everyone taking a survey has an option for them (or “other”)

57
Q

Aggregate data

A

all the data collected combined to create an average

58
Q

Microdata

A

the individual data collected from each case

59
Q

Metadata

A

technical information about how the information was collected

60
Q

Omnibus survey

A

multiple groups run one survey and get relevant information for them from it (to save money)

61
Q

Cross-sectional study

A

one-time question asked at one moment in time

62
Q

Longitudinal / Panel study

A

long-term study that asks multiple questions about a topic over time

63
Q

Non-response bias

A

people who agree to take the study may not accurately represent the population

64
Q

Research design

A

imposed controlled restrictions with the purpose of observation

65
Q

Experimental / Treatment group

A

the group given treatment before the post-test

66
Q

Control group

A

the group not given treatment (or given placebo) before the post-test

67
Q

Between-subjects design

A

doing the experiment without giving a pre-test

68
Q

Within-subjects design

A

giving both groups a pre-test to better contextualize the results of the post-test

69
Q

Internal validity

A

controlled space where you can be sure the outcome is a direct result of the treatment

70
Q

External validity

A

real world where the outside factors may influence the outcome

71
Q

Quasi-experiment

A

looking at statistics from the past to conduct an experiment as if it was happening now

72
Q

Factorial design

A

testing multiple factors, the sub categories within those factors, and how they relate to each other

73
Q

Double-blind design

A

both the participant and the administrator do not know if they are in the treatment group or the control group

74
Q

Single-blind design

A

only the participant does not know if they are in the treatment group or the control group

75
Q

Small-N research

A

qualitative approach, usually less than 30 cases

76
Q

Large-N research

A

quantitative approach, large number of cases

77
Q

Case study

A

in-depth investigation of a single individual, group, or event

78
Q

Descriptive case study

A

great detail of everything that happens in a case

79
Q

Theory-testing case study

A

cases that confirm of dispute current theories

80
Q

Failed most-likely case

A

case outcome is expected to confirm a theory, but it disproves it

81
Q

Successful least-likely case

A

case outcome is expected to disprove a theory, but it confirms it

82
Q

Process tracing

A

explaining each step of a case development to demonstrate the causation between 2 concepts

83
Q

Comparative research

A

small-N, contrasts cases to strengthen generalizations

84
Q

Most-similar-systems design

A

cases with the same factors that get different outcomes, so causation can not be proven

85
Q

Most-different-systems design

A

cases with different factors that get the same outcome, so causation can not be proven

86
Q

Galton’s problem

A

2 different things under observation may influence each other and lose their independence

87
Q

Audit trail

A

detailed description of the research steps taken

88
Q

Cross-tabulations

A

table used to compare 2 nominal or ordinal variables
- IV: row (across), DV: column (down)

89
Q

Descriptive statistics

A

statistics used to quantitatively describe information

90
Q

Inferential statistics

A

statics used to infer from a random probability sample to a population

91
Q

Univariate statistics

A

describes or infers a relationship between the value of 1 variable

92
Q

Bivariate statistics

A

describes or infers a relationship between the values of 2 variables

93
Q

Multivariate statistics

A

describes or infers a relationship between the value of 3 or more variables

94
Q

Frequency distribution

A

how many cases take each value (raw and relative)

95
Q

Raw frequency distribution

A

exact number of cases in each value

96
Q

Relative frequency distribution

A

proportion of cases in each value represented by a %

97
Q

Measure of central tendency

A

the most typical number (one number that represents the entire distribution)

98
Q

Measure of dispersion

A

how much the values vary

99
Q

Measures for nominal variables

A
  • Central tendency: mode (most) (value with greatest number of cases or highest %)
  • Dispersion: variation ratio (% of everything not in the modal category)
  • Association: Lambda (PRE-based), Cramer’s V (not PRE-based)
100
Q

Measures for ordinal variables

A
  • Central tendency: median (middle) (value of the middle case)
  • Dispersion: range (value of the lowest category to value of the highest category)
  • Association: Gamma (PRE-based), Tau-B (symmetrical table), Tau-C (asymmetrical table)
101
Q

Measures for Interval Ratio variables

A
  • Central tendency: mean (average) (average of all values, add values then divide by # of cases)
  • Dispersion: Standard deviation (average of all dispersions from the mean)
  • Association: Pearson’s R (linear data), Spearman’s RHO (non-linear data)
102
Q

Standardized scores

A

exact number of standard deviation units a case is above or below the mean

103
Q

Proportional Reduction in Error (PRE)

A

how much knowing the value of the cases in the IV helps you predict the values of the DV

104
Q

Basic linear regerssion

A

the regression line crosses the graph at the closest value to every point

105
Q

Intercept line

A

what number the regression line starts on the graph

106
Q

Type 1 error

A

assume that2 variables are related, but they are not

107
Q

Type 2 error

A

assume that 2 variables are not related, but they are

108
Q

Chi-Square

A

gives the likelihood of each possible degree of relationship occurring in a sample if there was no relationship in the population (nominal and ordinal only)

109
Q

Control variable

A

the variable that is unchanged to better understand the relationship between variables

110
Q

Statistical significance

A

how likely it is that a relationship between 2 variables in a sample might have occurred by chance and may not exist in the population

111
Q

Difference of means

A
  • T-Test: compares the means of 2 cases
  • ANOVA: compares the means of multiple cases

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