Psychology scientific investigation methodologies

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32 Terms

1

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?

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2

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.’

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3

Independent variable

-Experimental factor that is manipulated and changed.

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4

Dependent variable

-Experimental factor that is measured.

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5

Controlled variable

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

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6

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.

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7

Experimental group

-Group exposed to experimental condition (IV present).

-Determines if the IV made a change in DV.

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8

Research hypothesis

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

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

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9

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.

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10

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.

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11

Simulation

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

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12

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.

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13

Literature review

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

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14

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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15

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.

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16

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.

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17

Controlled experiment

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

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18

Between subjects

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

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19

Within subjects

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

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20

Mixed subjects

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

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21

Primary data

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

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22

Secondary data

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

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23

Quantitative data

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

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24

Qualitative data

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

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25

Objective data

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

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26

Subjective data

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

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27

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.

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28

Systematic errors

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

-Eg. faulty measurement instruments.

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29

Personal errors

-Fault or mistake by the researcher.

-Eg. forgetting someone’s questionaire.

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30

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.

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31

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.

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32

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.

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