Psychology scientific investigation methodologies

Research question

\-First step of a research investigation.

\-Phrased as a question & have two or more variables that will be tested to determine a cause-effect relationship.

\-eg. ‘does consuming smarties influence intelligence?

Aim

\-Statement or intent for a research topic.

\-Establishing a relationship between two variables.

\-Eg. ‘The aim is to investigate whether consuming smarties affects intelligence.’

Independent variable

\-Experimental factor that is manipulated and changed.

Dependent variable

\-Experimental factor that is measured.

Controlled variable

\-Variable that is considered to have an effect on the dependent variable so it is held constant to remove its potential effect.

Control group

\-Group is exposed to control condition (IV is absent).

\-Provides a comparison for experimental group to see if IV made changes in DV, or if it’s by chance.

Eg. Not consuming smarties.

Experimental group

\-Group exposed to experimental condition (IV present).

\-Determines if the IV made a change in DV.

Research hypothesis

\-Testable prediction of the relationship b/w 2 or more variables.

\-Needs to include: population, IV, prediction, DV & comparison to control condition

Correlational study

\-Planned observation and recording of behaviours that have not been manipulated or controlled.

\-Helps to understand the relationships that exist between variables to identify factors of greater importance and to make predictions.

Case study

\-An investigation of a particular activity, behaviour, event or problem that contains a real or hypothetical situation.

\-Includes complexities that would encountered in the real world.

Simulation

\-A process of using a model to study the behaviour of a real or theoretical system.

Fieldwork

\-Observing and interacting with a selected environment beyond the classroom, usually to determine correlation, rather than a casual relationshipp.

\-Used to capture human thoughts, feeling and behaviours.

Literature review

\-Collation and analysis of secondary data related to other people’s scientific findings.

Product, process or system development

\-Design or evaluation of an artefact, process or system to meet a human need, which may involve technological applications in addition to scientific knowledge and procedures.

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Modelling

\-Construction or manipulation of either a physical model, representation of an object, or a conceptual model that represents a system involving concepts that help people know, understand or simulate the system.

Classification and identification

\-Classification: arranging of phenomena, objects or events into manageable sets.

\-Identification: recognition of phenomena as belonging to particular sets or possibly being part of a new or unique set.

Controlled experiment

\-An experimental investigation of the relationship between one or more independent variables and a dependent variable, controlling all other variables.

Between subjects

\-Each participant is randomly allocated to one condition (group) only and each participant provides only one score for data analysis.

Within subjects

\-Each participant is involved in all conditions and provides multiple scores.

Mixed subjects

\-Combines features of both the between subjects and within subjects designs.

Primary data

\-Information collected directly from the researcher for their own purposes.

Secondary data

\-Information not directly collected by the current researcher; 2nd hand data from another person.

Quantitative data

\-Information that is expressed numerically; the quantity of what’s being studied.

Qualitative data

\-Non-numerical information involving the characteristics of a participant’s experience of what’s being studied.

Objective data

\-Information that’s observable, measurable, verifiable and **free from personal bias**.

Subjective data

\-Information based on personal opinion/interpretation/POV/judgements.

Random error

\-Errors due to some chance factor or chance variation in a measurement.

\-Eg. having a bad mood due to being hungry, affecting experiment.

Systematic errors

\-A measurement error produced by some factor that consistently favours one condition rather than another.

\-Eg. faulty measurement instruments.

Personal errors

\-Fault or mistake by the researcher.

\-Eg. forgetting someone’s questionaire.

Random sampling

\-A sample that fairly represents a population because each member has an equal chance of inclusion. \n -Eg. a school was the population and all students' names are listed and picked out a small amount using a computer program to participate. \n -Advantages: time effective, unbiased, equal chance. \n -Limitation: not a representative sample -> cannot be generalised.

Stratified sampling

\-Involves dividing the population into groups/strata based on specific categories and then selecting a sample from each strata in the same proportion they occur in the population. \n -Advantages: representative sample of population and findings likely to be valid and generalised. \n -Limitations: time consuming and lots of effort.

Convenience sampling

\-Selecting participants who are readily available without any attempt to make the sample representative of a population. \n -Eg. surveying people at the entry of a mall. \n -Advantage: cost and time effective, and easy for researchers. \n Limitation: not a representative sample -> cannot be generalised.