Scientific processes

aim

a general statement that describes the purpose of an investigation

hypothesis

a testable statement predicting the outcome at the start of a study

directional hypothesis

makes a clear anticipation of an experimental outcome

non directional hypothesis

states that there is a difference between conditions and groups but the nature is not specified

directional hypothesis is aka

one tailed

non directional hypothesis is aka

two tailed

null hypothesis

predicts no difference between variables

operationalisation of variables

clearly defining variables in terms of how they are being measured

extraneous variable

any other variable that is not the iv and affects the dv

extraneous variable example

age of participants, lighting in a lab

cofounding variables

any other variable that is not the iv and affects the dv that change systematically with the iv

demand characteristics

when participants guess the aim of the study and act accordingly

please u effect

participants act in a way to please the researcher

screw u effect

participants intentionally under perform to sabotage the study affecting validity

investigator effects

undesired influence of the investigator on the outcome of the research

eg of investigator effects

design of study, selection of participants

minimising investigator effects

randomisation ( reduces unconscious bias)

standardisation

using the exact same procedures and instructions for each participant

4 types of experiment

lab, natural, field , quasi

strengths of lab experiement

high internal validity, easy to replicate

limitations of lab experiment

may lack ecological validity, risk of demand characteristics

field experiement

the iv is manipulated in a natural setting

strength of field experiment

high mundane realism, reduces demand characteristics

limitations of field experiment

loss of control of extraneous variables, ethical issues- consent

natural experiments

researcher has no control over the iv

strengths of natural experiments

high external validity

limitation of natural experiment

natural events are rare, difficult to identify causation

quasi experiments

has an iv based on existing differences between people eg age

strengths of quasi experiment

easy to replicte

limitation of quasi experiment

extraneous variables, hard to infer causation

internal validity

the degree of confidence that the relationship being tested is not influenced by other factors

external validity

applying the conclusions of a study to context outside the study

mundane realism

how similar a study is to real life situations

experimental design

the way in which participants are arranged in an experiment

3 types of experimental design

independent groups
repeated measures
matched pairs

independent groups

when two seperate groups of participants experience two different conditions of the experiment

strengths of independent groups

reduces demand characteristics, order effects can be prevented

repeated measures

all participants experience both conditions of the experiment

strengths of repeated measures

no participant variables, cheap as you dont need many participants

weaknesses of repeated measures

order effects, demand characteristics

weakness of independent groups

participant variables, expensive , time consuming

matched pairs

participants are put into conditions based on similarity of backgrounds relevant to study

strengths of matched pairs

reduces participant variables

weakness of matched pairs

time consuming, expensive, cant fully eliminate individual differences

participant variables

individual differences between participants that could affect the dv

order effects

when a participant’s performance in one condition is affected by having already taken part in another condition.

eg of order effects

fatigue, practive

counterbalancing

reduces order effects by half or participants doing condition a then b then other doing b then a