Fundamental Terms Flashcards
Define aim
A statement of what the researcher intends to find out in a research study
Define null hypothesis
A statement which states there will be no difference
( if the data does not support your null hypothesis - you reject it and go with your alternative hypothesis )
Define directional hypothesis
States the directions of the difference or relationship
What the experimenter thinks will happen
Eg :
- more/ less
- higher/lower
- faster/slower
Define non directional hypothesis
States there is a difference between the conditionals or groups but the nature of the difference is not specified
Researcher is not sure what will happen & there is no previous research to suggest what the result might be
Define extraneous variables
Anything that Impacts the dependent variable that is not the independent variable
Define dependent variable
The thing that is measured/ will be affected by the changes
Define independent variable
The thing that is manipulated/changed
Eg. The different groups , the different conditions
Define debriefing
- A post research interview designed to inform participants of the tue nature of the study and to restore them to the state they were in at the start of the study
- may also gain useful feedback about the procedures used in the study
Define experiment
A research method where casual conclusions can be drawn because an independent variable has been deliberately manipulated to observe the casual effect on the dependent variables
Define hypothesis
A precise and testable statement about the assumed relationship between variables
Define operationalise
- Ensuring that the variables are in a form that Canberra easily tested
- being specific about what is being investigated
Define standardised procedures
A set of procedures that are the same for all participants in order to be able to repeat the study
Define External validity
The degree to which a research finding can be generalised
Define population validity
A type of external validity which can be generalised to other groups of people
Define historical validity
A type of external validity which can be generalised over time
Define internal validity
The degree to which an observed effect was due to the experimental manipulation rather than other factors such as confounding/ extraneous variables
Define mundane realism
- Refers to how a study mirrors the real world
- the research environment is realistic to the degree to which experiences encountered in the research environment will occur in the real world
What are independent groups design ?
- Participants are allocated to 2 or more groups representing different levels of the IV
- allocation is usually done using random techniques
Define counterbalancing
- An experimental technique used to overcome order effects when using a repeated measures design
- it ensures that each condition is tested first or second In equal amounts
Define matched pairs design
- Pairs of participants are matched in terms of key variables such as : age, IQ
- one member of each pair is allocated to one of the conditions under test and the second person is allocated to the other
What are advantages of matched pairs ?
- no order effects - there are different people in each condition
- participant variables - important differences are minimised through matching
What are disadvantages of matched pairs ?
Number of participants - need twice as many people compared to repeated measures
Practicalities - time consuming and difficult to find participants who match
Define repeated measures
There is only one group of participants this group takes part in both conditions
What are advantages of repeated measures ?
Participant variables - now the same people do the test in both conditions so any differences between individuals shouldn’t affect the results
Number of participants - fewer participants are needed to get the same amount of data
What are disadvantages of repeated measures ?
Order effects - of all participants did the ‘with audience’ conditions first any improvements in the second condition could be due to practice not the audience’s absence
Define confounding variables
Anything other than the IV has influenced your result which has not been accounted for before the experiment begins
Define alternative hypothesis
If the data forces you to reject your null hypothesis then you accept your alternative hypothesis
Advantages of independent groups design
No order effects - no one gets better through practice or gets worse through being bored or tired
Disadvantages of independent groups design
Participant variables - differences between the people in each group might affect the results
Number of participants - twice as many participants are needed to get the same amount of data compared to having everyone do both conditions
Demand characteristics
- There are aspects of a study which allow the participants to form an idea about its purpose
- if they think they know what kind of response the researcher is expecting from them they may show that response to please the researcher ( or do the opposite deliberately )
The conclusions drawn fro, the study would be invalid
Define social desirability bias
- people usually try to show themselves in the best possible light
- I’m a survey they may not be completely truthful but give answers that are more socially acceptable instead
= Make the results less valid
Co-variable
The two measured variables in a correlational analysis
The variables must be continuous
Intervening variable
A variable that comes between 2 other variables which is used to explain the association between those 2 variables
Define Single blind
- Participants are not aware of the condition they are in
- attempts to control for the confounding effect of demand characteristics
Define double blind
- Neither the participants or the researcher are aware of the aims of the investigation
- used in drug trials commonly
Independent variable
The one that changes
Variable that is directly manipulated by the researcher
Dependent variable
The one you measure
The variable that you think will be affected by changes in the independent variable
Operationalisation
Shows how the variables will be measured
- describing the process by which the variable is measured
- allows others to see exactly how you’re going to define and measure your variables
