Research Methods Flashcards

You may prefer our related Brainscape-certified flashcards:
1
Q

Code of Ethics (BPS)

A

The code focuses on four primary principles: respect, competence, responsibility and integrity

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

Briefing

A

A meeting at which information or instruction are given to people, before they do something, such as at an experiment

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

Debriefing

A

Used during an experiment in which some form of deception was necessary. After the experiment, all the information is given to the participant

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

Deception

A

Deception is when a researcher gives false information to subjects or intentionally misleads them about some key aspect of the research.

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

Stimulus presentation

A

Stimuli is presented to the participant, this can be tricky in online studies, as stimulus may present differently due to screen or resolution differences for example

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Outliers

A

An extreme observation or measurement, that is, a score that significantly differs from all others obtained.

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

Straightlining

A

occurs when survey respondents give identical answers to items in a battery of questions using the same response scale, i.e. giving the same response over and over again down a line of answers on a survey

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

Big Data

A

data that contains large (V)ariety, high (V)elocity, and increasing (V)olume

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

Data Scraping

A

A technique where a computer program extracts data from human readable output coming from another program

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

Data mining

A

the process of finding anomalies, patterns and correlations within large data sets to predict outcomes.

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

reactive research

A

People are aware that they are being studied, such as in an experiment or study

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

Non-reactive research

A

People are not aware that they are being studied, such as in an observational study

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

Systematic review

A

Detailed and comprehensive plan and search strategy appraising and synthesising all relevant studies on a particular topic

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

meta-analysis

A

Researchers combine the findings from multiple studies to draw an overall conclusion

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

Funnel plot

A

A visual tool for investigating publication and other bias in meta-analysis

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

Narrative synthesis

A

An approach to the systematic review and synthesis of findings from multiple studies that relies primarily on the use of words and text to summarise and explain the findings

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

grey literature

A

Research that is either unpublished or has been published in non-commercial form

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

descriptive statistics

A

Summarise and describe a given data set and give the central tendency and spread. they use concrete and known values

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

inferential statistics

A

Uses probability to infer and draw conclusions about a larger population from a smaller sample of data

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

nominal/categorical data

A

the lowest level of information, the data is split into categories, but there is no information about the numerical relationship between those categories

21
Q

ordinal data

A

Data ranked by positions in a group

22
Q

interval data

A

The distance between the data is on scale points, is continuous

23
Q

ratio data

A

continuous data that has a true zero and can’t take negative values, therefore it can be used in calculations

24
Q

central tendency

A

The most typical/representative score

25
Q

spread/dispersion

A

how much do the values vary around the central value

26
Q

mean

A

the arithmetic average

27
Q

median

A

the middle value, a point that divides a set of scores into equal halves

28
Q

mode

A

the score that occurs the most frequently

29
Q

range

A

The difference between the highest and lowest score -> very sensitive to outliers

30
Q

inter-quartile range

A

Data that is between the 25th and 75th percentile

31
Q

variance

A

the average squared deviation from the mean

32
Q

standard deviation

A

the square root of the variance, shows the average deviation from the mean

33
Q

normal distribution

A

A mathematically defined, theoretical distribution with a particular bell shape,
distribution is symmetrical on its middle axis

34
Q

skewness

A

the measure of asymmetry in distributions

35
Q

positive skew

A

most values are clustered at the low end of the scale

36
Q

negative skew

A

most values are clustered at the high end of the scale

37
Q

kurtosis

A

the peak and dispersion of the data

38
Q

leptokurtic

A

the distribution is more peaked

39
Q

platykurtic

A

the distribution is more dispersed

40
Q

empirical probability

A

uses the number of occurrences of a given outcome within a sample set as a basis for determining the probability of that outcome occurring again

41
Q

Big Q

A

Big Q refers to a broader, more philosophical approach to qualitative research. It involves examining fundamental questions about human behaviour, experience, and meaning. Researchers using the Big Q approach aim to understand complex phenomena in depth, exploring underlying meanings, patterns, and themes. Big Q research often involves open-ended inquiry, allowing participants to express their thoughts and experiences freely. It is concerned with understanding the “big picture” and uncovering the richness and complexity of human behaviour.

42
Q

small q

A

Small q refers to a more focused, empirical approach to qualitative research. It involves conducting detailed, systematic investigations of specific phenomena or research questions. Small q research often employs structured methods such as interviews, focus groups, or content analysis to collect and analyse data. Researchers using the small q approach aim to generate specific findings or insights that can contribute to existing knowledge in a particular area. Small q research may be more narrowly focused than Big Q research, but it still emphasizes depth and context in understanding psychological phenomena.

43
Q

Phenomenology

A

the individual personal perception of an experience of a phenomena

44
Q

Grounded Theory

A

Theory arises from the data

45
Q

Discourse Analysis

A

analysis of language, focus on content

46
Q

Thematic analysis

A

Researcher closely examines data to identify common themes, topics, ideas and patterns of meaning that come up repeatedly

47
Q

Grounded Theory

A

data come from interviews and participants observations and theory is developed from the data itself. important features include constant comparison of the data, flexibility and adjusting of the theory while analysing the data

48
Q

Interpretative Phenomenological Analysis (IPA)

A

rooted in phenomenology, and tries to understand individuals perception of their experience