AICE Psychology 1-30 Flashcards
Data in number form. An amount, measurement, time, or score. Also known as quantitative data.
Numerical 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.
Discrete data
This is data that could take any value between two given values.
Continuous data
Data
Primary data
Investigation looking for a causal relationship in which an IV is manipulated and is expected to be responsible for changes in the DV.
Experiment
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.
Independent Variable
Factor in an experiment which is measured and is expected to change under the influence of the IV.
Dependent 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.
Extraneous Variable
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).
Experimental condition
Level of the IV in an experiment from which the IV is absent. It is compared to one or more experimental conditions.
Control Condition
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.
Laboratory experiment
The way in which participants are allocated to levels of the IV.
Experimental design
Experimental design in which a different group of participants is used for each level of the IV (condition).
Independent measures design
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.
Demand Characteristics
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).
Random allocation
Experimental design in which each participant performs in every level of IV.
Repeated measures design
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.
Participant variables
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.
Order effects
Situation where participants’ performance improves because they experience the experimental task more than once, e.g., due to familiarity or learning the task.
Practice effect
Situation where participants’ performance declines because they have experienced an experimental task more than once, e.g., due to boredom or tiredness.
Fatigue effect
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.
Counterbalancing
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.
Matched pairs design
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.
Standardization
Extent to which a procedure, task or measure is consistent (It would produce the same results with the same people on each occasion).
Reliability
Extent to which the researcher is testing what they claim to be testing. (Accuracy)
Validity
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.
Field experiment
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.
Generalizability
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).
Ecological Validity
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.
Natural experiment
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
Uncontrolled variable
