Key Terms

Aims and Hypothesis

Key term	Definition
Aim	An aim identifies the purpose of the investigation.
Hypothesis	A hypothesis is a precise, testable statement of what the researchers predict/s will be the outcome of the study.
Alternative Hypothesis	The alternative hypothesis is the umbrella term for non-directional and directional hypotheses
Null Hypothesis	Thenull hypothesis predicts that there is no relationship between co-variables (correlation) OR no effect between the IV and DV (experiment). Example: There will be no effect on memory (10 picture recall test) when chewing gum compared to not chewing gum
One-Tailed Hypothesis Directional	A one-tailed directional hypothesis predicts a specific direction of the effect the IV has on the DV. Typically words such as increase, decrease, positive or negative are used. Example: There will be an increase in memory scores (10 picture recall test) when chewing gum compared to not chewing gum
Two-Tailed Hypothesis Non-directional	A two-tailed non-directional hypothesis predicts that the IV will have an effect on the DV, but the direction of the effect is not specified. Example: There will be an effect on memory scores (10 picture recall test) when chewing gum compared to not chewing gum

Variables

Key term	Definition
Variable	A factor or element within the study that is likely to change.
Independent Variable	The variable/s the experimenter manipulates (i.e. Changes).
Dependent Variable	A DV is the variable which is measured by the experimenter after they have manipulated the IV.
Extraneous Variables	Extraneous variables are other variables (not the IV) which could affect the results of the experiment e.g. the weather.
Confounding Variables	Additional variables (not the IV) which HAS affected your results of the experiment. The only way to get rid of a confounding variable is to redo the study and put something in place to control for it.

Experimental designs

Key term	Definition
Experimental design	The process of grouping your participants to represent the level of each IV
Independent measures design	Where each participant is only assigned to one condition of the IV. There are different participants in each condition.
Repeated measures design	Where each participant is assigned to more than one condition of the IV. The same participants take part in each condition.
Matched-pairs Design	There are equal groups where participants are matched based on certain characteristics e.g. gender, age…etc. For example, a participant in condition 1 who has an A grade in Maths, will be matched with another participant in condition 2 that has an A grade in maths.
Counter balancing	Also known as the ABBA effect.   AB – 4 participants: You will be completing the test in this order: Condition A: complete Stroop test with someone close to you Condition B: complete Stroop test with someone opposite you. BA – 4 participants: You will be completing the test in this order: Condition B: complete Stroop test with someone opposite you. Condition A: complete Stroop test with someone close to you Counterbalancing doesn’t get rid of the order effects, it works by ensuring that both groups have been effected by the order effects equally as much as each other. This means that the order effects are cancelled/balanced out.
Single blind test	This is when the participants are unaware of the condition that they are in. This means they are less likely to guess the aim of the study as they have not been given reasons or explanations as to the condition they are in. Therefore, reducing demand characteristics.
Double blind test	This is when neither the researcher or the participants are aware of which condition an individual is in. This ensures that demand characteristics are reduced from the participants, but also researcher bias is also reduced. Researcher bias is when the researcher intentionally or unintentionally influences the behaviour of the participants in order to get the participants to fit in with the results that they want. If the researcher is unaware of what condition it is, they would find it more difficult to influence.

Populations and Sampling

Key term	Definition
Participant	A person that takes part in the experiment or study.
Confederate	A confederate is an actor who participates in an experiment as a subject along with the other participant(s) i.e. they are acting as a participant without the awareness of the true participants.
Sample	A section of the population that is used to represent the group as a whole.
Self-selected AKA volunteer sampling	Participants sign up to a study after seeing an advertisement or invitation.
Random sample	Each participant of the study/experiment have an equal chance of being included in the sample.
Systematic sample	Participants of the study are selected in a logical way from a target population. For example, if 200 University students out of 2000 were required for a study, every 10th student from the University list/register would be selected.
Opportunity sample	Participants are selected based on who is available at the time and willing to participate.
Stratified sample	The researcher identifies the different types of people that make up the target population and works out the proportions needed for the sampleto be representative.

Experiments

Key term	Definition
Experiment	A scientific procedure undertaken to make a discovery, test a hypothesis, or demonstrate a known fact.
Laboratory Experiment	An IV is manipulated and a DV is measured under highly controlled and artificial conditions.
Field Experiment	An experiment carried out in the everyday environment (i.e. real life) of the participants. The experimenter still manipulates the IV, but the researcher has no control over extraneous variables.
Quasi Experiment	This is when the researcher does not manipulate the IV because it is naturally occurring within the participant. For example, age, gender, disability. A researcher cannot change your age, disability etc, therefore the IV is created by creating groups of participants with different levels of the IV.
Natural Experiment	Natural experiments are conducted in the everyday (i.e. real life) environment of the participants, but here the experimenter has no control over the independent variable as it occurs naturally in real life. For example, a psychologist noticed that a new leader in Madagascar had a huge impact on poverty. They decided to carry out a natural experiment by comparing crime rates (DV) before the leader was elected (decreased poverty) and after the leader was elected (increased poverty)

Observations

Key term	Definition
Observations	Observing of participants behaviour
Naturalistic observation	A research method where the participant’s behaviour is studied in a natural environment.
Controlled observation	Participant’s behaviour is usually observed in a controlled environment (laboratory) i.e. the surroundings are set up by the researcher in a very specific way.
Overt observations	The research is open with their participants about observing their behaviour. The participants know that they are being studied.
Covert Observations	The participants are unaware of the presence of the researcher and they are NOT made aware that their behaviour is being observed.
Participant observation	The observer takes part in the experiment with what the participants
Non-Participant Observation	The researcher observes participants without participating in the experiment itself.

Other research methods

Key term	Definition
Case Study	A piece of research carried out on a particular person, small group or situation over a long period of time.
Longitudinal Study	A method where data is gathered from the same participants over a period of time. This type of research can be as long as a few years to decades. Data will be collected a number of times over the time period of the study.
Attrition rates	This refers to when students drop out of the study. This tends to be more common in longitudinal research.
Snap-shot study	A piece of research which is carried out in one point of time – it provides a snap shot of behaviour.
Correlational study	A method where the researcher aims to look for relationships between two co-variables.
Cross-cultural study	The research of participants from different cultural groups.
Psychometric tests	A method of measuring participant’s mental characteristics; often gathering quantitative data.
Meta-analysis	A meta-analysis is where researchers combine the findings from multiple studies to draw an overall conclusion.

Interviews and questionnaires

Key term	Definition
Interview	An interview is a conversation where questions are asked and answers are given.
Structured interview	Each interview has a set of pre-planned questions and they are presented with exactly the same questions in the same order.
Unstructured Interviews	Questions in this style of interview are not prearranged. The questions are made up on the spot at the time of the interview and tend to build on what the participants have said.
Questionnaires	A set of written questions with a choice of answers, devised for the purposes of a survey or statistical study.
Open–ended questions	Are questions which obtain qualitative data by asking questions which cannot be answered with a simple one-word answer.
Closed-ended questions	Are questions which can be answered with a simple one-word answer e.g. “yes” or “no”.
Rating scales	Requires participants to answer a question by selecting a value (number) to reflect their perception on a topic.
Likert rating	This is a type of question that measures the attitude of individuals. An attitude statement is given and individuals have to select the statement most suited to them.
Response Bias	Where participants tick boxes on a questionnaire without paying attention. This can be an issue for longer questionnaires that use rating scales and Likert scales. In other words, response bias occurs when people answer test items in ways that do not align with their true attitudes, beliefs, thoughts, or behaviours.

Data

Key term	Definition
Primary Data	First-hand information that has been collected by the researcher for the purpose of their study.
Secondary data	The researcher uses pre-existing data. The data could have been from a newspaper, diary entry or even data collected by another researcher or study.
Qualitative data	Descriptive data – language – words
Quantitative data	Numerical data
Nominal	Data that is put into categories
Ordinal	Data that has an end point and the point between each data set is unequal.
Interval	Data has the capacity to be infinite and the point between each data set is equal.

Sources of bias

Key term	Definition
Gender bias	The emphasis of the study is more inclined to one gender.
Cultural bias	The emphasis of the study is more inclined to one ethnicity/culture.
Enthocentricism	The researcher uses their own ethnicity for judgement about other groups.
Eurocentricism	Psychologists place emphasis on European theories/ideas at the expense of those of other cultures.
Age bias	The emphasis of the study is more inclined to a certain age group.
Experimenter bias	The researcher influences the results in order to portray a certain outcome.
Observer bias	The researcher’s cognitive bias causes them to subconsciously influence the participants of an experiment.

Reliability and Validity

Key term	Definition
Reliability	The overall consistency of the measure or study. This can then lead to consistency of results.
Internal Reliability	Assesses the consistency of results across items within a test.
External Reliability	This assesses consistency when different measures of the same thing are compared i.e. does one measure match up against another measure e.g. comparing to halves of a test, or two researchers comparing results for inter-rater reliability.
External reliability: Inter-rater reliability	The method of measuring the external consistency of a test. This method is carried out by different “raters” giving consistent estimates/measures of behaviour – if there is a concordance of 0.8 between the researchers/observers, then the test is said to have high inter-rater reliability.
External reliability: Test Re-test reliability	The test-retest method assesses the external consistency of a test. Examples of appropriate tests include questionnaires and psychometric tests. It measures the stability of a test over time. A typical assessment would involve giving participants the same test on two separate occasions. If the same or similar results are obtained then external reliability is established.
Validity	Refers to the accuracy of a test’s ability to measure what it is supposed to measure.
External Validity	Whether the findings will generalise to other populations, locations, contexts and times and still hold true.
External Validity: Ecological validity AKA Mundane realism	Refers to the extent to which the findings of a research study are able to be generalised to real-life settings.
External Validity: Population Validity	How representative the sample used is to other populations.
External Validity: Historical/Temporal Validity	Will the findings still be valid as society changes over the years e.g. will a study conducted about female behaviour in 1965, generalise to females today?
Internal Validity	Within your measure, the IV is the only variable effecting the DV.
Internal Validity: Face Validity	The degree to which a procedure, especially a psychological test or assessment, appears effective in terms of its stated aims.
Internal Validity: Concurrent Validity	Whether a measure produces similar results for a participant as another test that claims to measure the same thing e.g. a participant completes a brand-new test for autism and gained very similar results in a previously well-established test of autism.
Demand Characteristics	A subtle cue that makes participants aware of what the experimenter expects to find or how participants are expected to behave– they then change their behaviour according to these beliefs.
Observer Effect	Refers to subjects altering their behaviour when they are aware that an observer is present.
Social Desirability	Describes the tendency of survey respondents to answer questions in a manner that will be viewed favourably by others.
Type 1 error	The incorrect rejection of a true null hypothesis (a “false positive”). The researcher believes that there is an effect when actually there is not one.
Type 2 Error	Incorrectly retaining a false null hypothesis (a “false negative”). The researcher believes there is no effect when actually there is.