Experimental methods

• Research methods


  Different techniques used to conduct psychological research
• Experiments are just one type of research method that follow a specific set of rules
• Independent variable (IV)


  The thing the experimenter changes or manipulates
• Dependent variable (DV)


  The thing the experimenter measures to see the effect of the IV
• Operationalization


  Making variables in a form that can be easily tested
• Dependent variable


  Scores received for the homework task
• Hypothesis


  A statement about what you expect to find in your research
• There are two types of hypothesis: directional and non-directional
• Characteristics of a good hypothesis


  • Operationalized variables
  • States the relationship between IV and DV
  • Includes a comparison between conditions
• Directional hypothesis


  States what the expected difference will be between conditions
• Non-directional hypothesis


  States there will be a difference between conditions, but doesn't specify what the difference will be
• Directional hypothesis


  • Participants who complete the essay whilst watching frozen will achieve a lower mark than participants who complete the essay in a quiet room
• Non-directional hypothesis


  • There will be a difference in the marks achieved between participants who complete the essay whilst watching frozen and participants who complete the essay in a quiet room
• Aim


  • To investigate whether confidence levels in children affect their levels of obedience
• Operationalized IV


  • Condition 1: Children scoring above 50 on a confidence questionnaire
  • Condition 2: Children scoring below 50 on a confidence questionnaire
• Dependent variable


  • Amount of instructions from a teacher followed in a 60 minute lesson
• Non-directional hypothesis


  • There will be a difference in the amount of instructions from a teacher followed during a 60 minute lesson between children who score over 50 on a confidence questionnaire and children who score under 50
• Aims to test the hypothesis that there is an association between two variables
• The independent variable (IV) is manipulated by the experimenter, while the dependent variable (DV) is measured as a result of this manipulation.
• Correlation does not imply causation - it only shows that there is some relationship between the two variables being studied.
• Correlation coefficient (r) - A measure of how closely related two sets of data are, ranging from -1 to +1.
• Participants are randomly assigned to one of several groups or conditions based on the level of the IV they receive.
• Positive correlation - When both variables increase or decrease together, e.g., height and weight.
• Each group receives a different level of the IV, allowing researchers to compare the effects of these different levels on the DV.
• Pearson's correlation coefficient r measures the strength and direction of linear relationships between continuous numerical data.
• Negative correlation - When one variable increases as another decreases, e.g., age and number of friends.
• Random assignment ensures that any differences observed between groups can be attributed to the effects of the IV rather than other factors such as age, gender, or previous experience.
• Negative correlation - As one variable increases, the other decreases; r = -1 indicates perfect negative correlation.
• Values close to zero indicate weak correlations, while closer to ±1 suggest stronger associations.
• Positive correlation - As one variable increases, so does another; r = +1 indicates perfect positive correlation.
• Random assignment ensures that any differences observed in the results can be attributed to the effect of the IV rather than other factors such as pre-existing characteristics of participants.
• r values range from -1 to +1, with negative numbers indicating inverse or opposite relationships and positive numbers indicating direct or same relationships.
• No correlation - No clear pattern or relationship between the two variables; r = 0 indicates no correlation.
• Negative correlation - When one variable increases while the other decreases, e.g., age and reaction time.
• No correlation - No clear pattern or relationship between the two variables; r = 0 indicates no correlation.
• Double blinding helps prevent demand characteristics influencing results.
• Experimenters must ensure that participants do not know which group they have been allocated to, known as double blind procedure.
• Negative correlation - When one variable increases as another decreases, e.g., age and number of siblings.
• Random assignment ensures that any differences observed between groups can be attributed to the effect of the IV rather than pre-existing differences among participants.
• The random assignment ensures that any differences observed between the groups are due to the effect of the independent variable rather than other factors.