The manipulation of the independent variable to measure the effect on the dependent variable.
Aim
A general statement of what research intends to investigate.
Hypothesis
A testable statement that states the relationship between 2 variables.
Directional Hypothesis
-States the direction of the difference or relationship
-Has been previousresearch conducted before - uses words like 'more', 'less', '[adjective]..er' e.g. fewer
Non-directional hypothesis
-Does not state the direction of the difference or relationship.
-No previous research conducted before - uses words like 'difference' or 'effect'.
what else can non directional and directional hypothesis be called/referred to?
also known as two-tailed or one-tailed.
Null hypothesis
States there is no difference or relationship between the variables being studied.
Independent Variable
The variable that is manipulated by the researcher so that the effect on the dependent variable can be measured.
Dependent Variable
The variable that is being measured by the researcher (due to the changes of the IV)
Levels of independent variable(s)
To test the effect of IV we need to compare the 2experimental conditions - we need 2 levels of the independent variable.
Control Condition
condition that is not exposed to the variable that is changed.
Experimental Condition
condition that includes exposing the partial points to the change.
Operationalism
clearly defining the variable in terms of how they can be measured.
Extraneous variables (SPIDO)
any variables other than the IV that may affect the DV e.g age,gender (nuisance variable)
Extraneous variables
participant variables - individual differences between ppts that may affect the DV
Extraneous variables
situational variables - any feature of the experimental situation that may affect the DV
Confounding variables
any other variable (other than IV) that has affected the DV
Demand characteristics
any cue from the researcher or research situation that can be interpreted by participants as revealing the purpose of the investigation leading them to changing their behaviour to please/sabotage experimenter or results.
Hawethorne Effect
changing behaviour due to the attention of taking part in a study
Investigator effects
any effect of the investigator's behaviour on the DV. this may include anything from the design of the study to the interaction with ppts during the research process.
Order effects
when the positioning or order of conditions influence the outcome (you learn therefore repeat it faster/bored)
Controlling variables
investigator effects (r) - RANDOMISATION
using chance when designing materials and deciding the order of conditions e.g randomly assimilated list of words
Controlling variables - investigator effects (s) - STANDARDISATION
using exactly the same formalised procedures and instructions for all ppts
e.g all ppts given same rules
Experimental design
the way in which ppts and variables are distributed in order to make comparisons about DV performance
Dealing w/ Ppt variables random allocation
use a random method to decide which ppt goes into which group e.g flipping a coin
COMMON MISCONCEPTION WITH RANDOM ALLOCATION AND RANDOMISATION
random allocation - to do with allocating ppts
randomisation - to do with the materials used in study
Dealing with Order effects counterbalancing
half ppts experience the conditions in one order and the other half in the opposite order
e.g ppt 1: condition 1 - condition 2
ppt 2 : condition 2 - condition 1 etc.
(ABBA)
Independent groups
separate groups of ppts for each condition in the study
strengths of independent groups
no order therefore no order effects
less likely to guess aim of study
weaknesses of independent groups :
pptsvariables
small sample: hard to generalise
time consuming + expensive: more ppts are needed
Repeated measures
all ppts take part in all conditions - two sets of results for each ppt are then compared
strengths of Repeated measures:
control over ppt variables
fewer ppts needed
weaknesses of Repeated measures
order effects
demand characteristics (figure out aim)
Matched pairs
pairs of ppts are matched in terms of key variables e.g age and IQ. one member from each pair is placed into one of the conditions and the other is placed into the other.
strengths of Matched pairs
no order effects
control over ppt variables
weaknesses of Matched pairs:
time consuming
not possible to control all ppt variables
Laboratory experiment
variables and conditions are highly controlled + involved artificialmaterials carried out in an environment e.g lab
strengths of Laboratory experiment :
controlled - accurately assess IV + higher int. validity
replicable - high reliability due to high control
weaknesses of Laboratory experiment
lacks eco validity
involvement of researcher in manipulating and controlling variables make findings not easily generalised.
Field experiment
carried out in a natural setting (anywhere outside lab)