Research in psychology1.3 Experimental methods

VariablesA variable is any characteristics or factor that can vary, e.g:

gender, age, grade points, stress, motivation, etc.

Independent variable- the IV produce a change in another variable- deliberately manipulated by the researcher - all other variables are kept constant- Example: new antidepressant medication

Dependent variable- measured after alteration of the IV- is it influenced by the IV?- Example: Did the medication affect the depression?

OperationalizedOperational definition translates an abstract term

(variable) into something observable and measureable.

The operational definition gives the variable meaning within a particular study.’

- In precise terms, what is being measured?- Example: aggression vs. how many times the participant will kick the doll during one hour

HypothesisExperimental hypothesis is a prediction of how the IV will affect the DVExample: the new therapy will decrease the participants anxiety more

than the old oneA null hypothesis is prediction that there will be no changeExample: The new therapy will have no effect on the participants anxiety compared to the old one

Most often two conditions:Experimental (treatment) condition

- Situation where a variable is being manipulated

Control condition - Situation where a variable is not being manipulated

Is there a significant difference between the two?

Be a thinker p. 27Identify the Independent variable and

dependent variable in each of the following experimental hypothesis.

PlaceboPeople who receiving a treatment show a

change in behaviour because of their expectations, not because the treatment itself had any specific benefit

CaseStudy on the effect of the new antidepressant drug

One group receives the new antidepressant drug and told they receive it – experimental condition (treatment group)

One group receives a placebo pill but told they receive the new antidepressant drug – control condition (group)

Does the antidepressant work better than the placebo?

ExperimentsLaboratory experiments

+ easy to replicate+ easy to hold variables constant- artificial environment- low ecological validity

Field experiments+ Ecological validity- hard to hold variables constant

Natural experiment+ Unique situations- No control over variables

ExperimentsLaboratory experiments

Example:Study on the effect of the new antidepressant drug

Field experimentsExample: Piliavin and Rodin (1969) in the New York subway – investigated helping behaviour regarding sober or drunk person

Natural experimentExample: aggression before and after TV came,

stroke victims

Confounding variables (undesirable variables that influence the IV and DV)

Demand Characteristics (aka Hawthorne effect, taken from the Hawthorne Works plant of Western Electric in the US)

- Participants act differently because they are in a study and trying to guess what the researcher is after

- To counteract: Use single blind control: participants are not told the aim

Confounding variablesResearcher bias (observer bias)

- When expectations of the researcher affects the findings, often in subtle and unintentional ways

- To counteract: Use double blind control in which both participant and experimenter are unaware if the participant is in the control group or the experimental group

Confounding variablesParticipant variabilityWhen characteristics of the sample affect the

dependent varible

To counteract: use random sampling

Correlation studies – an experiment cannot be carried out but data are collected which show a relationship

Data is gathered that relates to the IV and the DVIf one variable change the other change as well

Positive correlation:- Same change in both variables- both in increase or both decrease- Example: Life expectancy and hours of exercise+ 1 = perfect positive correlation

Negative correlation:- When one variable increase the other decrease- Education and time in jail- minus 1 = perfect negative correlation

Correlation studiesExample:

1. Researcher measures one variable (wealth)2. Researcher measures a second variable (happiness)3. The researcher statistically determines whether wealth and happiness are related.

+

Bidirectional ambiguityCause-and-effect?Example: Better social relationships and greater

happiness are correlated

But, which causes which?

Better social relationships = greater happiness or

Greater happiness = better social relationshipsor

is there that another variable responsible for the behaviour?

Correlation between eating ice cream and drowning?

= ?