Psychology AICE Vocabulary: Key Terms & Definitions

Numerical data

data in number form. An amount, measurement, time, or score. Also known as quantitative data.

discrete data

this is data that can only take certain values, for example, that number of children in a class, goals scored in a match, or red cars passing a point.

Numerical data

data in number form. An amount, measurement, time, or score. Also known as quantitative data.

discrete data

this is data that can only take certain values, for example, that number of children in a class, goals scored in a match, or red cars passing a point.

continuous data

this is data that could take any value between two given values.

primary data

data

Experiment

Investigation looking for a causal relationship in which an IV is manipulated and is expected to be responsible for changes in the DV.

Independent Variable

Factor under investigation in an experiment which is manipulated to create two or more conditions or levels and is expected to be responsible for changes in the DV.

Dependent Variable

Factor in an experiment which is measured and is expected to change under the influence of the IV.

Extraneous Variable

Either acts randomly, affecting the DV in all levels of the IV or systematically, i.e. on one level of the IV (called a confounding variable) so can obscure the effect of the IV, making the results difficult to interpret.

Experimental condition

one or more of the situations in an experiment which represent different levels of the IV and are compared (or compared to a control condition).

Control Condition

Level of the IV in an experiment from which the IV is absent. It is compared to one or more experimental conditions.

Laboratory experiment

RM~There is an IV, a D, and strict controls. It looks for a causal relationship and is conducted in a setting that is not in the usual environment for the participants with regard to the behavior they are performing.

Experimental design

the way in which participants are allocated to levels of the IV.

Independent measures design

Experimental design in which a different group of participants is used for each level of the IV (condition).

Demand Characteristics

Features of the experimental situation which give away the aims. They can cause participants to try to change their behavior, e.g., to match their beliefs about what is supposed to happen, which reduces the validity of the study.

Random allocation

Way to reduce the effect of confounding variables such as individual differences. Participants are put in each level of the IV (ea. person has an equal chance of being in any condition).

Repeated measures design

Experimental design in which each participant performs in every level of IV.

Participant variables

Individual differences between participants (such as age, personality and intelligence) that could affect their behavior in a study. They could hide or exaggerate differences between levels of the IV.

Order effects

Practice and fatigue effects are consequences of participating in a study more than once like a (RMD). Cause changes in performance between conditions that are not due to the IV, so can obscure the effect on the DV.

Practice effect

Situation where participants' performance improves because they experience the experimental task more than once, e.g., due to familiarity or learning the task.

Fatigue effect

Situation where participants' performance declines because they have experienced an experimental task more than once, e.g., due to boredom or tiredness.

Counterbalancing

Used to overcome order effects in an RMD. Each possible order of levels of the IV is performed by a different sub-group of participants. Can be described as an ABBA design, as half the participants do condition A then B and half do B then A.

Matched pairs design

Experimental design in which participants are arranged into pairs. Each pair is similar in ways that are important to the study and one member of each pair performs in a different level of the IV.

Standardization

Keeping procedure for each participant in an experiment (or interview) exactly the same to ensure that any differences between participants or conditions are due to the variables under investigation rather than differences in the way they were treated.

Reliability

Extent to which a procedure, task or measure is consistent (It would produce the same results with the same people on each occasion).

Validity

Extent to which the researcher is testing what they claim to be testing. (Accuracy)

Field experiment

Investigation looking for a causal relationship in which an IV is manipulated and is expected to be responsible for changes in the DV. Conducted in the normal environment for the participants for the behavior being investigated.

Generalizability

Apply the findings of a study more widely, e.g., to other settings and populations. They take the following forms: Population validity and ecological validity.

Ecological Validity

Extent to which the findings of research in one situation would generalize to other situations. Influenced by whether the situation, such as a lab, represents the real world effectively and whether the task is relevant to real life (has mundane realism).

Natural experiment

Investigation looking for a causal relationship (IV cannot be directly manipulated by experimenter). Instead, they study the effect of an existing difference or change. Since the researcher cannot manipulate the levels of the IV, it is not a true experiment.

Uncontrolled variable

Confounding variable that may not have been identified and eliminated in an experiment, which can confuse the results. It may be a feature of the participants or situation

Self~report

RM such as a questionnaire or interview, which obtains data by asking participants to provide information about themselves.

Questionnaires

RM that uses written questions.

Closed questions

Questionnaire, interview or test items that produce quantitative data. Have only a few stated alternative responses and no opportunity to expand on answers.

Open questions

Questionnaire, interview or test item that produce qualitative data. Participants give full and detailed answers in their own words, i.e. no categories or choices are given.

Inter~rater reliability

Extent to which two researchers interpreting qualitative responses in a questionnaire or interview, will produce the same records from the same raw data.

Social desirability bias

Trying to present oneself in best light by determining what a test is asking.

Filler questions

Items put into a questionnaire, interview or test to disguise the aim of the study by hiding the important questions among irrelevant ones so that participants are less likely to alter their behavior by working out the aims.

Interview

RM using verbal questions asked directly (face to face, or on the phone).

Structured interview

Interview with questions in a fixed order which may be scripted. Consistency might also be required for the interviewer's posture, voice, etc. so they are standardized.

Unstructured interview

Interview in which most questions (after the first one) depend on the respondent's answers. A list of topics may be given to the interviewer.

Semi~structured interview

Interview with a fixed list of open and closed questions. Interviewer can add more questions if necessary.

Subjectivity

Personal viewpoint, which may be biased by one's feelings, beliefs or experiences, so may differ between individual researchers. It is not independent of the situation.

Objectivity

Unbiased external viewpoint that is not affected by an individual's feelings, beliefs or experiences, so should be consistent between different researchers.

Naturalistic observation

Study conducted by watching the participants' behavior in their normal environment without interference from the researchers in either the social or physical environment.

Controlled observation

Study conducted by watching participants' behavior in a situation in which the social or physical environment has been manipulated by the researchers. Can be conducted in either the participants' normal environment or in an artificial setting.

Unstructured observation

Study in which the observer records the whole range of possible behaviors, which is usually confined to a pilot stage at the beginning of a study to refine the behavioral categories to be observed.

Structured observation

Study in which the observer records only a limited range of behaviors.

Behavioral categories

Activities recorded in an observation. Should be operationalized (clearly defined) and should break a continuous stream of activity into discrete recordable events. They must be observable actions rather than inferred states.

Inter~observational reliability

Consistency between two researchers watching the same event, i.e. whether they will produce the same records.

Participant observer

Researcher who watches from the perspective of being part of the social setting.

Non~participant observer

Researcher who does not become involved in the situation being studied, e.g. by watching through one~way glass or by keeping apart from the social group of the participants.

Overt observer

Role of the observer is obvious to the participants.

Covert observer

Role of the observer is not obvious, e.g. because they are hidden or disguised.

Correlation

RM which looks for a causal relationship between two measured variables. A change in one variable is related to a change in the other (although these changes cannot be assumed to be causal).

Positive correlation

Relationship between two variables in which an increase in one accompanies an increase in the other, i.e. the two variables increase together.

Negative correlation

Relationship between two variables in which an increase in one accompanies a decrease in the other, i.e. higher scores on one variable corresponds with lower scores on the other.

Hypothesis(es)

Testable statement predicting a difference between levels of the IV (in an experiment) or a relationship between variables (in a

Alternative hypothesis

Testable statement which predicts a difference or relationship between variables in a particular investigation.

Non~directional (two~tailed) hypothesis

Statement predicting only that one variable will be related to another, e.g. that there will be a difference in the DV between levels of the IV in an experiment or that there will be a relationship between the measured variables in a correlation.

Directional (one~tailed) hypothesis

Statement predicting the direction of a relationship between variables, e.g. in an experiment whether the levels of the IV will produce an increase or a decrease in the DV or in a correlation whether an increase in one variable will be linked to an increase or a decrease in another variable.

Null hypothesis

Testable statement saying that any difference or correlation in the results is due to chance, i.e. that no pattern in the results has arisen because of the variables being studied.

Operationalization

Definition of variables to that they can be accurately manipulated, measured or quantified and replicated. This includes the IV and DV in experiments and the two measured variables in correlations.

Situational variable

Confounding variable caused by an aspect of the environment, e.g. the amount of light or noise.

Control

Way to keep a potential extraneous variable constant, e.g. between levels of the IV, to ensure measured differences in the DV are likely to be due to the IV, raising validity.

Population

Group sharing one or more characteristics from which a sample is drawn.

Sample

Group of people selected to represent the population in a study.

Sampling technique

Method used to obtain the participants for a study from the population.

Opportunity sample

Participants are chosen because they are available, e.g. university students are selected because they are present at the university where the research is taking place.

Volunteer (self~selected) sample

Participants are invited to participate, e.g. through advertisements via email or notices. Those who reply become the sample.

Random sample

All members of the population (i.e. possible participants) are allocated numbers and a fixed amount of these are selected in an unbiased way, e.g. by taking numbers from a hat.

Quantitative data

Numerical results about the quantity of a psychological measure such as pulse rate or a score on an intelligence test.

Qualitative data

Descriptive, in~depth results indicating the quality of a psychological characteristic, such as responses to open questions in self-reports or case studies and detailed observations.

Measure of central tendency

Mathematical way to find the typical or average score from a data set using the mod, median or mean.

Mode

Measure of central tendency that identifies the MOST frequent score(s) in a data set.

Median

MCT that identifies the MIDDLE score of a data set which is in rank order (small~large). If there are two numbers in the middle they are added together and divided to two.

Mean

MCT calculated by adding up all the scores and dividing by the number of scores in the data set.

Measure of spread

Mathematical way to describe the variation or dispersion within a data set.

Range

Difference between the biggest and smallest values in the data set + one (a measure of spread).

Standard deviation

Calculation of the average difference between each score in the data set and the mean. Bigger values indicated greater variation (a measure of spread).

Test~Retest

Measures consistency. Used twice (if participants' two sets of scores are similar, it has good reliability.

Bar chart

Graph used for data in discrete categories and total or average scores. There are gaps between each that is plotted on the graph because the columns are not related in a linear way.

Histogram

Graph used to illustrate continuous data, e.g. to show the distribution of a set of scores. It has a bar for each score value, or group of scores, along the x~axis. The y~axis has frequency of each category.

Scatter graph

Way to display data from a correlational study. Each point on the graph represents the point where one participant's score on each scale for the two measured variables cross.

Normal distribution

Even spread of a variable that is symmetrical about the mean, median and mode. The graph showing this distribution is sometimes called a "bell curve" because of its shape. The graph of the frequency of each score or value rises gradually and symmetrically to a maximum at the point of the mean, median and mode.

Ethical issues

Problems in research that raise concerns about the welfare of participants (or have potential for a wider negative impact on society).

Ethical guidelines

Pieces of advice that guide psychologists to consider the welfare of participants and wider society.

Informed consent

Knowing enough about a study to decide whether you want to agree to participate.

Right to Withdraw

Participant should know that they can remove themselves, and their data, from the study at any time.

Privacy

Participants' emotions and physical space should not be invaded, for example, they should not be observed in situations or places where they would not expect to be seen.

Confidentiality

Participants' results and personal information should be kept safe and not released to anyone outside the study.

Debriefing

Giving participants full explanation of the aims and potential consequences of the study at the end of a study so that they leave in at least as positive a condition as they arrived.

Protection

Participants should not be exposed to any greater physical or psychological risk than they would expect in their day~to~day life.

Deception

Participants should not be deliberately misinformed (lied to) about the aim or procedure of the study. If this is unavoidable, the study should be planned to minimize the risk of distress, and participants should be thoroughly debriefed.