MS3553 Revision notes Flashcards
(145 cards)
1
Q
What is Research?
A
A systematic process to investigate a phenomenon and increase knowledge with a clear purpose and timeline.
2
Q
Define Mode 0 Research.
A
Knowledge shaped by power/patronage, e.g. Pharma industry influence over studies.
3
Q
What characterizes Mode 1 Research?
A
Traditional academic research – linear, theoretical, peer-focused.
4
Q
Define Mode 2 Research.
A
Practice-based, collaborative research across disciplines, aimed at real-world application.
5
Q
What is Evidence-Based Practice?
A
Using best available research evidence + professional expertise + context to guide decision-making.
6
Q
What is a Systematic Review?
A
A structured evaluation of existing research to find patterns, strengths, and gaps.
7
Q
Define Hypothesis.
A
A specific, testable prediction derived from theory or observation.
8
Q
What does Research Design entail?
A
A plan detailing how data will be collected, measured, and analysed.
9
Q
What is Generalisation in research?
A
Extent to which findings apply to other settings, people, or times.
10
Q
Define Practitioner Approach.
A
Research rooted in experience, less formal, often intuitive or model-based.
11
Q
What is a Scientific Approach?
A
Structured and methodical, usually involving hypothesis testing and measurable outcomes.
12
Q
What are Ethical Issues in research?
A
Considerations like informed consent, confidentiality, and researcher responsibility.
13
Q
What is Research Ideation?
A
The creative process of developing and refining research ideas, often iterative and non-linear.
14
Q
Define Reflexive in the context of research.
A
Continuously questioning and examining your role, assumptions, and influence on the research process.
15
Q
What does Reflective mean in research?
A
Thoughtfully considering ideas, experiences, and literature to shape your research focus.
16
Q
What does Feasibility refer to in research?
A
Whether your research project is practical and achievable within time, skills, access, and resources.
17
Q
Define Appropriateness in research.
A
How well your topic aligns with academic objectives, theory, your degree requirements, and personal goals.
18
Q
What is Business Impact?
A
The real-world application or benefit of research to organisations, practices, policies, or society.
19
Q
Define Academic Impact.
A
Theoretical or methodological contributions made to a specific discipline or area of study.
20
Q
What is Mind Mapping?
A
A brainstorming tool to visually map ideas, concepts, and connections to develop a coherent research question.
21
Q
What is the Contribution to Knowledge?
A
The value your research adds by filling a gap, confirming, extending, or challenging current theory.
22
Q
What is the purpose of a Literature Review?
A
A critical, analytical summary of existing research on a topic that helps frame your own study.
23
Q
What does Framing the Literature involve?
A
Structuring literature to support an argument that justifies your research question.
24
Q
Define Funnel Structure in literature reviews.
A
A way to write literature reviews: start broad and narrow down to specific theories or gaps.
25
What is Meta-Analysis?
Combines statistical findings from multiple studies to identify overall trends or effects.
26
What is Critical Thinking?
The ability to question, evaluate and reflect on information with clarity, depth, and relevance.
27
Define Ontology in research.
Assumptions about the nature of reality – whether it exists independently or is socially constructed.
28
What does Epistemology study?
The study of knowledge — how we know what we know; the rules and logic of acquiring knowledge.
29
Define Axiology.
The role of values and ethics in the research process; considers the researcher's relationship to the research.
30
What is Positivism?
A belief that reality is objective and can be observed and measured; typically linked to quantitative research.
31
What does Interpretivism focus on?
A belief that reality is socially constructed and best understood through qualitative methods exploring meaning.
32
Define Deductive Reasoning.
Theory → Hypothesis → Data. Test existing theory with empirical evidence.
33
What is Inductive Reasoning?
Data → Patterns → Theory. Build theory based on observed patterns.
34
What does Reflexivity mean in research?
The researcher’s awareness of their own influence on the research process, including biases and assumptions.
35
What is Research Design?
A strategic plan or 'route map' outlining how to collect, analyse, and interpret data to answer a research question.
36
Define Measurement in research.
Standardised method of capturing or quantifying information.
37
What does Reliability refer to?
Whether a study would produce the same results if repeated.
38
Define Validity.
Whether the study measures what it claims to measure.
39
What is Replicability?
Ability to reproduce the study following the same process.
40
What is Cross-sectional Design?
Collecting data from multiple cases at one point in time.
41
Define Longitudinal Design.
Repeated measurements over time from the same sample to detect changes.
42
What does Experimental Design involve?
Manipulating variables to observe effects, includes control group.
43
What is Quasi-Experimental Design?
Similar to experimental, but lacks full control or random assignment.
44
Define Case Study Design.
In-depth analysis of a single case, often qualitative.
45
What is Mixed Methods research?
Combines both qualitative and quantitative methods for a fuller understanding.
46
What does Triangulation mean in research?
Using multiple methods or data sources to cross-check results.
47
What is the Research Onion?
A framework to structure research design choices.
48
What is the difference between research design and research methods?
Design = strategy (overall blueprint); Method = tool/technique (e.g. interviews, surveys)
49
What influences the choice of research method?
Choice depends on:
* Type of data (numeric vs narrative)
* Complexity of research question
* Philosophical position (positivist, interpretivist, etc.)
50
What are the core evaluation criteria in research?
Criteria include:
* Reliability
* Validity
* Replicability
* Generalisability
51
What is an experimental research design?
Full control, random assignment; Rare in business – more in controlled trials
52
What is a quasi-experimental design?
No random assignment; Useful when variables like age/gender can't be manipulated
53
What is a cross-sectional study?
One-time data collection across cases; For comparative or correlational studies
54
What is a longitudinal study?
Repeated data over time; To assess changes, trends, or intervention impact
55
What is a time-series study?
Advanced longitudinal stats method; For regular interval tracking (e.g. daily sales data)
56
What is a case study in research design?
In-depth on one unit (e.g. firm); When you want deep context, not generalisation
57
What does mixed methods design combine?
Combines qualitative and quantitative methods; When your question needs both depth and breadth
58
What is triangulation in mixed methods?
Cross-verify results using different methods
59
What are the essential steps after choosing a research design?
Steps include:
* Prepare materials
* Identify participants
* Ensure ethical approval
* Collect data
* Analyse findings
* Write up recommendations
60
What is a research question (RQ)?
A clearly defined question that guides the focus, purpose, and structure of a research study
61
What are research objectives?
Specific, actionable steps taken to achieve the aim and answer the research question
62
What is a hypothesis?
A testable prediction often used in quantitative studies (null vs alternative hypotheses)
63
What is a systematic review?
A structured analysis of the literature to refine a research question and identify knowledge gaps
64
What is conceptualisation in research?
The process of refining abstract ideas into specific concepts or variables suitable for research
65
What criteria make a good research question?
Criteria include:
* Clear
* Researchable
* Theory-connected
* Focused
* Original
* Feasible
66
What is the purpose of qualitative research?
To understand the social world through interpretation of people’s experiences, behaviours, and contexts
67
What is interpretivism in research?
A philosophical stance where reality is seen as socially constructed; knowledge is derived from human experience
68
What is reflexivity in qualitative research?
Ongoing reflection on how the researcher’s background, assumptions, and presence affect the research
69
What is credibility in qualitative research?
Trustworthiness of the research findings — achieved through good practice and triangulation
70
What does transferability mean in qualitative research?
Extent to which findings may be applied to other contexts — supported by rich descriptions
71
What is the Hawthorne Effect?
When participants change behaviour because they know they’re being studied
72
What is informed consent in research ethics?
Participants must be fully informed of the study’s purpose, risks, and their rights before agreeing to take part
73
What are vulnerable populations in research?
Groups who may be at greater risk in research, such as children, mentally unwell, or marginalised groups
74
What is non-maleficence in ethical principles?
Do no harm
75
What is the Nuremberg Code?
Foundation of modern research ethics, established post-WWII response to horrific Nazi experiments
76
What is the difference between formal access and informal access in research?
Formal access requires official permission from an organisation; Informal access involves gaining cooperation from individuals
77
What is the significance of power differentials in research?
Imbalances between researcher and participant can lead to pressure or exploitation
78
What is the purpose of a case study in qualitative research?
In-depth, contextual research of a real-life phenomenon using multiple methods
79
What is the inductive approach in qualitative research?
Building theory from data collected during research rather than testing pre-existing theories
80
What is the difference between probability and non-probability sampling?
Probability sampling gives every individual an equal chance of selection; Non-probability sampling does not
81
What is generalisability in research?
The extent to which findings from a sample apply to the broader population
82
What is sampling error?
A difference between the sample and the population that distorts results
83
What are the types of qualitative data?
Types include:
* Observations
* Interviews
* Focus Groups
* Written Data
* Critical Incidents
* Life Histories
84
What are Gathering Methods?
Tools for collecting qualitative data (e.g. interviews, focus groups)
## Footnote
Gathering methods are essential for qualitative research, allowing researchers to obtain in-depth insights from participants.
85
Define Data Collection Frameworks.
Structured strategies using multiple methods (e.g. case studies, ethnography)
## Footnote
Data collection frameworks guide researchers in systematically gathering data.
86
What are Interviews in qualitative research?
Structured conversations with participants to explore experiences or perspectives
## Footnote
Interviews can vary in structure from informal chats to formal sessions.
87
What are Focus Groups?
Group discussions used to gather collective views and insights
## Footnote
Focus groups leverage group dynamics to elicit richer data.
88
What are Participatory Methods?
Data is gathered by participants themselves (e.g. photo diaries, artefacts)
## Footnote
These methods empower participants and can yield unique perspectives.
89
Define Case Study.
In-depth, contextual research of a real-life phenomenon using multiple methods
## Footnote
Case studies provide comprehensive insights into complex issues.
90
What is Ethnography?
Immersive research into cultural or organisational life through direct involvement and observation
## Footnote
Ethnography requires long-term engagement with the subject.
91
What is Grounded Theory?
A method of building theory from data via constant comparison and theoretical sampling
## Footnote
This approach allows for theories to emerge directly from the data collected.
92
Define Discourse Analysis.
Examines language use, meaning-making, and how reality is constructed through talk/text
## Footnote
Discourse analysis focuses on how communication shapes social realities.
93
What is Template Analysis?
A flexible form of thematic analysis that uses a coding template to interpret textual data
## Footnote
It allows researchers to adapt their analysis to the data context.
94
What are the two main components of Qualitative Research Structures?
* Data Gathering
* Data Analysis
## Footnote
These components can function independently or as part of a larger framework.
95
What are the types of Interviews?
* Ethnographic
* Informant
* Respondent
* Narrative
* Focus Group
## Footnote
Each type serves different research purposes and contexts.
96
What is the purpose of Participatory Methods?
Allow participants to document their own experience
## Footnote
This approach enhances reflexivity and creativity in qualitative work.
97
What is the Case Study Method best used for?
* Longitudinal studies
* Organisational processes
* Behavioural change in context
## Footnote
Case study methods are particularly effective in exploring complex phenomena.
98
What are the features of Ethnography?
* Immersive
* Actor-centred
* Long-term
* Contextual
## Footnote
Ethnography provides rich descriptions of social interactions.
99
Define Grounded Theory.
Build theory directly from the data (Glaser & Strauss)
## Footnote
Grounded theory emphasizes the connection between data collection and theory development.
100
What is the purpose of Discourse Analysis?
Examine how language constructs meaning and social reality (Silverman)
## Footnote
Discourse analysis studies how language shapes perceptions and interactions.
101
What is Thematic Analysis?
A flexible method for identifying, analysing, and reporting patterns (themes) within qualitative data
## Footnote
Thematic analysis is widely used for its adaptability across various qualitative research designs.
102
What constitutes a Theme in qualitative research?
A recurring pattern of meaning, relevant to the research question, developed from codes in the data
## Footnote
Themes help researchers interpret and explain the dataset.
103
What is Inductive Coding?
Data-driven; themes emerge from the data itself
## Footnote
Inductive coding allows for a more organic development of themes.
104
What is Deductive Coding?
Theory-driven; themes are guided by pre-existing concepts or frameworks
## Footnote
Deductive coding is often used when researchers start with a theoretical framework.
105
What are the phases of Thematic Analysis according to Braun & Clarke?
* Familiarisation
* Coding
* Searching for Themes
* Reviewing Themes
* Defining & Naming Themes
* Producing the Report
## Footnote
Each phase is crucial to ensure a systematic approach to thematic analysis.
106
What should you consider when Evaluating Themes?
* Do these themes capture the core meaning of the data?
* Are they coherent across the dataset?
* Do they answer the research question?
* Are they too broad or too narrow?
* Is anything missing or overlapping?
## Footnote
Evaluating themes helps ensure relevance and clarity in the analysis.
107
What is Survey Research?
A quantitative method for collecting data using structured questions to describe, explain, or compare attitudes, behaviours, or characteristics
## Footnote
Survey research is vital for gathering data from large populations efficiently.
108
What is a Questionnaire?
A structured set of questions used to collect data in surveys
## Footnote
Questionnaires ensure consistency in data collection.
109
Define Closed-Ended Question.
A question with predefined response options (e.g. Yes/No, Likert scale)
## Footnote
Closed-ended questions simplify data analysis.
110
What is an Open-Ended Question?
A question allowing respondents to answer in their own words
## Footnote
Open-ended questions can provide richer qualitative insights.
111
What is a Likert Scale?
A rating scale measuring agreement or frequency (e.g. Strongly agree to strongly disagree)
## Footnote
Likert scales are commonly used in survey research to assess attitudes.
112
What is a Double-Barrelled Question?
A question that asks about two issues at once (e.g. 'Do you think the service is fast and reliable?')
## Footnote
Double-barrelled questions can confuse respondents and skew results.
113
What is a Leading Question?
A question that suggests a preferred response
## Footnote
Leading questions can bias the results and should be avoided.
114
What are the types of Survey Questions?
* Open-Ended
* Closed-Ended
* Dichotomous
* Category/List
* Likert Scale
* Ranking Scale
* Semantic Differential
## Footnote
Each type serves a specific purpose in data collection.
115
What are the recommended principles for good survey questions?
* Clear
* Neutral
* Mutually exclusive
* Exhaustive
## Footnote
These principles help ensure clarity and effectiveness in surveys.
116
What is Quantitative Research?
A method involving numerical data to test hypotheses, identify patterns, and generalise findings
## Footnote
Quantitative research often relies on statistical methods for analysis.
117
Define Variable in quantitative research.
Any measurable attribute that can vary (e.g. income, motivation)
## Footnote
Variables are fundamental to quantitative analysis, influencing the outcomes of research.
118
What is a Conceptual Framework?
A diagram or model outlining relationships between variables in your research
## Footnote
Conceptual frameworks help clarify the research design and guide analysis.
119
What are the types of Quantitative Research?
* Descriptive
* Correlational
* Experimental
* Quasi-Experimental
## Footnote
Each type serves different research objectives and methodologies.
120
What is the purpose of a Measurement Scale?
The way in which variables are quantified and categorised (nominal, ordinal, interval, ratio)
## Footnote
Measurement scales are essential for data analysis and interpretation.
121
What is Univariate Analysis?
Examines one variable at a time (e.g. frequencies, means)
## Footnote
Univariate analysis provides insights into individual variables.
122
What is Bivariate Analysis?
Explores relationships between two variables (e.g. correlation, t-tests)
## Footnote
Bivariate analysis helps identify associations between variables.
123
What is Multivariate Analysis?
Analyses relationships involving more than two variables
## Footnote
Multivariate analysis is useful for complex data relationships.
124
What is the Chi-Square Test?
A statistical test for identifying associations between categorical variables
## Footnote
The Chi-Square Test is commonly used in survey research to analyze categorical data.
125
What is a T-Test?
Compares the means of two groups to test for significant differences
## Footnote
T-Tests are essential for assessing differences in quantitative research.
126
What does Correlation measure?
Measures the strength and direction of a relationship between two continuous variables
## Footnote
Correlation analysis helps understand the relationships between variables.
127
What does the Square Test compare?
Distributions across groups (categorical data)
## Footnote
The Square Test is used to determine if there is a significant difference between the expected and observed frequencies in categorical data.
128
What does Correlation measure?
Strength/direction between continuous variables
## Footnote
The correlation coefficient (r value) indicates the strength and direction of a linear relationship between two continuous variables.
129
What does a T-Test compare?
Means between two groups
## Footnote
A T-Test helps determine if there is a significant difference between the means of two independent groups.
130
What does ANOVA stand for and what does it compare?
Analysis of Variance; compares means across 3+ groups
## Footnote
ANOVA is used when comparing three or more groups to see if at least one group mean is different from the others.
131
What do Crosstabs do?
Break down data by multiple variables
## Footnote
Crosstabs help to analyze the relationship between two or more categorical variables.
132
What are Bar & Pie Charts used for?
Visual data representation
## Footnote
These charts help in presenting categorical data visually for easier interpretation.
133
What is the purpose of the Chi-Square Test?
Test for association between two categorical variables
## Footnote
The Chi-Square Test assesses whether observed frequencies differ from expected frequencies under the null hypothesis.
134
What is the null hypothesis in a Chi-Square Test?
No relationship
## Footnote
The null hypothesis suggests that there is no association between the two categorical variables being tested.
135
When do we reject the null hypothesis in a Chi-Square Test?
If p < 0.05
## Footnote
A p-value less than 0.05 indicates a statistically significant association.
136
How is the Chi-Square Test accessed in software?
Analyze → Descriptive Statistics → Crosstabs → Statistics → Chi-Square
## Footnote
This is a common pathway in statistical software for running a Chi-Square Test.
137
What does the r value indicate in Correlation?
Strength and direction (e.g. -0.182 = weak negative)
## Footnote
The r value ranges from -1 to 1, where values close to -1 indicate a strong negative correlation, values close to 1 indicate a strong positive correlation, and values around 0 indicate no correlation.
138
What does p < 0.05 indicate in Correlation?
The relationship is statistically significant
## Footnote
A p-value below 0.05 suggests that the observed correlation is unlikely to have occurred by chance.
139
How is the Correlation Test accessed in software?
Analyze → Correlate → Bivariate
## Footnote
This pathway is used in statistical software to conduct a correlation analysis.
140
What does a T-Test indicate if p < 0.05?
Significant difference
## Footnote
A p-value less than 0.05 in a T-Test suggests that the means of the two groups being compared are statistically significantly different.
141
How is the T-Test accessed in software?
Analyze → Compare Means → Independent Samples T-Test
## Footnote
This is the common pathway in statistical software to execute an Independent Samples T-Test.
142
What are the 3 Vs that define Big Data?
* Volume – massive scale
* Velocity – real-time/streaming speed
* Variety – structured + unstructured data
## Footnote
The 3 Vs are essential characteristics that distinguish Big Data from traditional data.
143
What are common sources of Big Data?
* Social media
* IoT
* Online transactions
* Sensors
## Footnote
These sources generate large volumes of data that can be analyzed for insights.
144
What tools are commonly used for Big Data?
* Hadoop
* Spark
* NoSQL
* Machine Learning
## Footnote
These tools facilitate the storage, processing, and analysis of large datasets.
145
What are some applications of Big Data?
* Marketing
* Healthcare
* Finance
* Logistics
* Smart cities
## Footnote
Big Data applications span various industries, providing insights that drive decision-making and efficiency.
