PS1107 - Psychological research skills 2

Independent variable

• Specific factor that the experimenter manipulates or changes to see its effect

• For example in a study on caffeine and memory the amount of caffeine given to the participants

Dependent Variable

• the outcome variable that researchers measure

• It is assumed to be affected by the changes made to the IV

• Such as performance score on a caffeine study

Levels of an independent variable

• the different values or conditions used for the independent variables

• E.g 0mg, 50mg and 100mg for caffeine study - IV has three levels

Extraneous variables

• extra factors that have the potential to affect the dependent variable

Confounding variable

• when an extraneous variable changes systemically along with an independent variable

• Provides a alternative explanation for results

Does correlation equal causation?

• no - just because two things change together does not mean one caused the other

Why is establishing cause and effect important?

• helps us know exactly why things happen which allows for better real world interventions

• E.g if we know sleep causes better grades we can encourage more sleep to improve student performance

What three things have in a ‘true experiment’

• manipulates an independent variable

• Holds all other variables constant - to control for extraneous factors

• Measures the change in the dependent variable

Control group

• provides a baseline measure of what happens without the specific treatment or intervention

• Allows researchers to compare the treated groups results to a normal state

Placebo group

• receives an inert treatment with no active ingredients

• Helps researchers see if the results are caused by the participants expectations of an effect rather than the treatment itself

Independent samples design

• involves randomly allocating participants to different groups where each person only takes part in one condition

Weakness of independent samples

• participant variables (individual differences)

• Different people are in each group differences in results might be due to the people themselves rather than he IV

Repeated measures design

• uses the same participants for every condition of the experiment

• This eliminates differences between participants as a factor

What are order effects and how do you fix them

• occurs when the sequence of tasks affects the results (e.g participants get better with practice or worse due to boredom)

• Can be fixed with counterbalancing which means half the participants do condition a then b while the other half does b then a

Matched pairs design

• method where participants are paired up based on specific characteristics (like IQ or age) that might interfere with results ensuring the groups are equal before the experiment starts

Quasi-Experiment

• Used when it is impossible or unethical to randomly assign participants to groups

• Includes studying differences based on age, gender or pre-existing medical conditions like limb amputation

Pro’s of online experiments

• easy to recruit large diverse groups quickly

• Can be done when face to face testing is impossible

Con’s of online experiments

• no control over the participants environment

• Not practical for physical tasks like exercise or tasting food

• Potential technical glitches