Research methods in psychology

Field experiments

• Quantitive

• “In the real world”

• Cannot control for extraneous variables and cannot be easily replicated

• Ethics: often not practical to get informed consent, no debriefing (usually)

Quasi and natural experiments

• Quantitive

• Grouped based on traits or behaviour

• do not show direct causation, but they are able to imply a causal relationship between an IV and a DV

Lab experiment

• Quantitive

• Control for extraneous variables

• Can have low ecological validity

Natural experiment

• Similar to quasi

• Refers to an IV that is environmental and outside of the control of the researcher

• Pre-test, post-test design

• Do not show direct causation, but they are able to imply a causal relationship between an IV and a DV

True experiment

• IV is manipulated and a DV is measured under controlled conditions

• Participants are randomly allocated to conditions

Extraneous variables

• Undesirable variables that influence the relationship between the IV and DV

Demand characteristics

• When participants act differently because they know that they are in a study

• May try to guess the aims of the study and act accordingly

Researcher bias

• When the experimenter sees what they are looking for

• The expectations of the researcher consciously or unconsciously affect the findings of the study

Double-blind control

• Avoid researcher bias

• Participants do not know whether they are in the experimental or control group

• Scientist carrying out the experiment does’t know the aim of the study, nor which group is the treatment and which one is the control group

Participant variability

• The range of differences among individuals in a study, including demographics, experience, and behavior

Artificiality

• When the situation created is so unlikely to occur that one has to wonder if there is any validity in the findings

Positive correlation

• When both variables are affected in the same way

• As x increases, y increases

Negative correlation

• As one variable increases, the other decreases

Bidirectional ambiguity

• When it is unclear whether variable A causes variable B or vice versa, making it difficult to determine the direction of causality