Unit 11: Research Methods Flashcards
What is the acronym for evaluating studies and theories?
Generalisability
Reliability
Applications
Validity
Ethical Consideration
Independent variable (IV)
the variable directly manipulated by the researcher.
Dependent variable (DV):
the variable being measured in a study.
Operationalisation:
making the variables in an investigation detailed and specific.
Extraneous variable:
a variable that is not controlled which could affect the results of a study.
Confounding variable:
an extraneous variable that affects the results of the study so that the effect of the IV is not truly being seen.
Situational variable:
an extraneous variable present in the environment of the study.
Order effects:
when participants improve or worsen in the second condition because they have practised or become fatigued.
Demand characteristics:
when the participant alters their behaviour in response to the perceived aims of the investigation.
Investigator effect:
when a researcher unintentionally gives clues to participants altering their behaviour.
Participant variables:
extraneous variables specific to the participants of an investigation for example their mood
Standardised procedure:
where the procedure of a study is the same across all conditions.
Counterbalancing:
where half of the participant group experience condition A then condition B while the other half experience condition B then condition A.
Randomisation:
when participants are randomly assigned to condition A or B as their first or second test condition.
Single-blind technique:
when information about the study is withheld from participants.
Double-blind technique:
when the aims of the study are withheld from both participants and researchers.
Random allocation:
when participants are randomly assigned to a condition of the study.
Null hypothesis:
a prediction that the results will fail to show any difference (or relationship) that is consistent or systematic.
Alternative (experimental) hypothesis:
a prediction of the outcome of a study based on what is expected to happen.
Directional hypothesis:
a hypothesis that predicts the direction the results will go in.
Non-directional hypothesis:
a hypothesis that predicts that a difference/relationship will be found but does not specify what the difference/relationship will be.
Experimental hypothesis:
the name given to a hypothesis when used in field and laboratory experiments.
Target population:
the group of people being investigated in a study.
Sample:
a selection of the target population that is directly studied in an investigation.
Generalisability:
the extent to which the results of a study represent the whole population not just the sample used.
Sampling method:
a technique used to gather a representative group of people as a sample from the target population.
Random sampling technique:
a technique used to gather a random sample of participants from the target population.
Stratified sampling technique:
a technique that ensures subgroups of the target population are proportionately represented in a sample.
Sample error:
when a sample differs in qualities from the target population it intends to represent.
Volunteer sampling technique:
a technique that asks for participants by placing an advert for volunteers.
Biased sample:
when the sample recruited is made up of a particular type of person which may not reflect the target population.
Opportunity sampling technique:
a technique that recruits participants who are readily available at the time.
Research design:
how participants are allocated to the conditions of a study.
Experimental design:
the name given to research design when used in an experiment.
Independent measures design:
participants are split into groups with each group tested in only one condition of a study.
Repeated measures design:
the same participants are used in all conditions of a study.
Matched pairs design:
different participants are used in each condition of the study but are matched for likeness on important characteristics.
Reliability:
the consistency of an outcome or result of an investigation (a measure).
Validity:
whether the test measures what was intended.
Internal validity:
whether the measures used in a test genuinely test what they were designed to test.
External validity:
whether the findings are generalisable to the target population.
Qualitative methods:
ways of conducting research that find out new information rather than testing a prediction; often resulting in gathering qualitative data.
Researcher bias:
when a researcher interprets the outcome of a study according to their own view (subjective).
Triangulation:
when more than one measure is taken for a behaviour to cross-validate the findings.
Objective:
not open to interpretation unbiased.
Quantitative methods:
ways of conducting research that test a prediction and gather quantitative data.
Ethical issues:
researchers follow codes or rules of conduct when carrying out research to protect participants from harm.
Right to withdraw:
ensuring that participants are clearly aware of their right to leave the study at any point.
Interview:
a research method designed to gather self-reported information from participants.
Structured interview:
a set of pre-set questions asked to a respondent.
Interview schedule:
a list of set questions around the study aim.
Semi-structured interview:
a mix of pre-set questions and unprepared questions asked to a respondent.
Unstructured interview:
a free-flowing conversation around a particular topic with a respondent.
Social desirability bias:
during an interview a respondent may answer a question in a way that is deemed socially acceptable.
Interviewer effect:
the characteristics of an interviewer impact the way a respondent answers questions.
Questionnaires:
a self-report technique designed to ask lots of people questions about a topic.
Closed-ended questions:
questions with a fixed response to choose from.
Open-ended questions:
questions with no fixed response.
Correlation:
a way of analysing relationships between variables.
Co-variables:
two variables that can be plotted against each other to indicate the type of relationship between them.
Positive correlation:
as one co-variable increases the other co-variable increases.
Negative correlation:
as one co-variable increases the other co-variable decreases.
Case study:
a study of a single person group or event.
Observation:
a research method that involves watching and recording behaviour.
Naturalistic observation:
an observation conducted in an everyday environment where the behaviour being studied is normally seen.
Controlled or structured observation:
an observation carried out in a laboratory or controlled environment.
Overt observation:
participants know they are being observed as part of an investigation.
Covert observation:
participants are unaware that they are being observed.
Participant observation:
when an observer is involved in the group they are observing.
Non-participant observation:
the observer watches and records people without being actively involved.
Significant figures:
digits that have meaning in a number and signify a level of accuracy.
Estimate:
do a quick rough calculation of what the results are showing.
Ratios:
compare one thing against another to show proportions.
Fractions:
a way of cutting something up to show proportions.
Percentage:
a fraction of 100 found by multiplying a fraction by 100.
Descriptive statistics:
ways of summarising data to make raw data easier to understand. Descriptive statistics include the mean, median, mode, range and also graphs
Raw data:
the results themselves without analysis
Range:
the difference between the highest and lowest score in a set of data to show the spread of scores.
Measure of dispersion:
a way of showing the spread of scores and variability.
Mode:
in a set of numbers the most common one (the one found most often).
Bi-modal:
when there are two modes in a set of numbers.
Multi-modal:
when there is more than two modes in a set of numbers.
Median:
the middle score in a set of numbers.
Mean/arithmetic mean:
the average of a set of numbers found by adding them all up and dividing the result by how many original numbers there were.
Normal distribution:
when mean, median and mode are very similar or the same.
Skewed distribution:
when median and/or mode differ from the mean.
Frequency scores:
the number of times each score is found in a dataset.
Frequency table:
shows how often each score in a dataset is found using tallying.
Tally:
a way of recording each instance of something using a vertical mark for each instance.
Frequency diagram/histogram:
illustrates frequency to show the distribution of continuous data.
Bell curve:
the shape of a normal distribution curve.
Bar chart/graph:
a graph to show categories of data; a way of summarising data which can then be compared.
x-axis:
horizontal line along the base of a chart/graph.
y-axis:
vertical line at the side of a chart/graph.
Scatter diagram:
a graph used to illustrate a relationship or correlation between two variables to see if they co-vary.
Line of best fit:
a line on a scatter diagram through the centre of a cluster of points to see if there is a correlation and in which direction (negative or positive) it is.
Primary data:
data collected directly for a specific research purpose.
Secondary data:
data used in a study that have already been collected often for a different purpose.
Meta-analysis:
a procedure used to merge and analyse findings from studies focusing on a similar issue in order to draw overall conclusions.
Qualitative data:
data that are descriptive not numbers
Quantitative data:
numerical data.
Participatory:
research that involves children and young people from the start including the design and data-gathering phases
Participation rights:
the rights of people including children
Protection rights:
the rights of a child to be protected at all times.
