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counfounds
Difficult to control for. You cannot control what happens in the participant’s life in between conditions for example.
counterbalancing
Where half of the participants complete condition A first, followed by condition B, and the other half of your participants complete condition B first, followed by condition A.
Example: matched pair designs
Researchers recruit 100 people and form 50 pairs based on similar age and gender. One person in each pair is assigned a new diet, while the other follows a standard diet to measure weight loss differences.
mixed measures designs
Combines qualitative and quantitative data collection and analysis within a single study to provide a more comprehensive understanding of a research problem.
random sampling
Participants selected at random from target population.
Time consuming
stratified sampling
Target population spil into subcategories. The split participants in the sample habe to be representative of members in the target audience (e.g. if ¼ of population has blue eyes, then ¼ of the participants should have blue eyes (if relevant to the research)).
Time-consuming
systematic sampling
Participants selected in an orderlt fashion (e.g., from 500 people every fifth person in the list).
Difficult to emplot (you need the list of participants to begin with).
opportunity sampling
Selects participants who are available at the time, so can be called convenience sampling.
Efficient and economical
Likely to form samples that are unrepresentative of the population and which can be heavily biased by the researcher.
purposive sampling
Researcher starts with a purpose in mind, and purposefully targets a specific type of participant, excluding any participants who do not fit the intended characteristics.
Biases and unrepresentative sample.
volunteer sampling
Participants are volunteers who habe actively chosen to take part in the study. Also known as a self-selecting sample.
snowball sampling
Participants are asked to recommend other potential participants to take part in the study.
cross-sectional study
Also called snapshot study.
An observational research mehod that analyses daya from a population or subset at a single, specific point in time.
Is a correlational study related to causality?
Correlation does NOT imply causality.
The three types of transcription:
Orthographic → write down exactly, word for word what participant said.
Playscript → edited for readability and impact, usually removing fillers, false starts, and grammatical inaccuracies.
Non-orthographic → also focuses on how participants used language to convey meaning.
Interpretative Phenomenological Analysis (IPA)
Interested in the individual experience of the participants and the meanings that these experiences have for the individuals (qualitative).
Appropriate choice of analysis if you were planning to work with a very small sample size.
grounded theory
Describes the process of drawing themes from qualitative data, taking perscpective into consideration.
We do not start with a theory, but rather arrive at a theory as a result of the analysis, so the process is very much data driven.
discourse analysis
The study of language in social contexts - it is about what people are doing with their language, or what they are trying to achieve with their speech.
We are interested in the words that people choose to use and how they use them.
reflexivity
Being able to reflect on your influence over the data as a researcher.
scientific (journal) articles
Scopus
PsycInfo
Pubmed
statistics (population, country-, regional-level indicators, etc.)
Statista
Eurostat
data and reports from companies, industry sectors, IGOs, NGOs
Policy Commons
NexisUni
ProQuest
Bonferroni correction formula
alpha(new) = 0.05/number of tests
Example:
5 tests → alpha = 0.01
Harder to het significance (harder to make a Type 1 error)
ontology
Nature of reality/ Theory of existence
epistemology
Nature of knowledge / Theory of knowledge (what do we know and how do we know what we know?
methodology
Theory of method/ How do we gain knowledge?