CHAPTER 4: RESEARCH METHODS

Theory

- an idea/ thought that intends on explaining something

Variable

- a factor that can change or is able to change in an experiment/ investigation

Independent variable

- variable that is manipulated/ controlled by the experimenter

Dependent variable

- measured outcome (behavior) of this change

Hypothesis

A testable prediction, often implied by a theory

Three things a hypothesis needs to contain

- Both conditions of the independent variable and dependent variable
- An exact prediction of the study's outcome
- Relationship or difference between the two varaiables

Operationalizing [hypotheses]

- when variables in an experiment are defined in order to manipulate the IV and the DV

Alternative hypothesis

- states the predicted difference between the start of the investigation and the result (the predicted outcome)

Null hypothesis

- states that there is no difference between the start of the investigation and the result (there is no outcome)

Non-directional hypothesis

- only the fact that there is a difference between variables is stated

Directional hypothesis

- the difference in outcome between the two variables is stated

Quantitive Data

- a fixed set of responses

Strength of Quantitative Data

- easy to analyse and draw conclusions
- less room for interpretation: reduces the chance of bias

Weakness of Quantitative Data

- lacks depth, not reflecting real-world complexity
- does not reflect how complex the real world is (less validity)

Qualitative Data

- starts out in a form that cannot be initially counted (such as paragraphs and pictures)

Strength of Qualitative Data

- more depth and detail
- seen to have more validity (the respondant is free to fully express their thoughts and feelings)

Weakness of Qualitative Data

- difficult to analyse and summarize
- conclusions are rawn depending on the researcher's own opinions: open to bias

Primary Data

- collected first hand by the researchers, so the data matches the aims of the study

Strength of Primary Data

- suits the aims of the research, so more useful
- authentic (it comes first hand from the participants)

Weakness of Primary Data

- it takes time and effort to collect, and is costly (as the researcher has to design the procedure, test it, and find participants to use)

Secondary Data

- analyzed and collected by another researcher (therefore, it already exists)

Strength of Secondary Data

- easy to access and the data is already checked (research involves very little effort and much less expense)

Weakness of Secondary Data

- it may not fit what the researcher is investigating
- it might be out of date, incomplete, or of poor quality

Laboratory experiment

- an experiment that is conducted in a controlled environment

Strengths of a labratory experiment

- EVs can be controlled, so cause and effect is established
- use of standardized procedures makes it easier for the procedure to be tested again which can confirm validity

Weaknesses of a laboratory experiment

- behavior in lab is less 'normal', which makes it difficult to generalize (reducing validity)
- participants may change their behavior because they are aware of being watched

Field experiment

- an experiment that is conducted in a natural setting where the experimenter manipulates the independent variable

Strengths of a field experiment

- more realistic than lab experiments as it is conducted in a natural environment (high validity)
- can use standardized procedures which allows for some control

Weaknesses of a field experiment

- may lose control of EVs so difficult to show cause and effort
- ethical issues because participants are not aware of the fact that they are being studied

Natural experiment

- an experiment that is conducted in a natural or laboratory setting where the experimenter does not manipulate the independent variable because it would change anyways

Strengths of a natural experiment

- has high validity because it involves real-world variables that normally take place in a natural setting
- when teh DV is being measured in a laboratory, there can be a high level of control over EVs

Weaknesses of a natural experiment

- few opportunities to do this kind of research as behaviors may be rare
- There may be EVs because the researcher cannot randomly allocate participants to IV conditions

Extraneous variables

- any variable apart from the independent variable that can affect the dependent variable

Reliability

- the consistency of an experiment/ a measurement

Validity

- whether a result is "true" or not/ is it accurate

Ecological validity

- how true/ accurate something is in terms of how it applies to the real world

Demand characteristics

- If the participants know the aims of the investigation, they may change their behavior - for example, they might want to help the researcher achieve their aims. This means that their behavior is not realistic.

Independent Measures Design

- participants are allocated to different groups where each group represents one experimental condition

Strength of an independent measures design

- order effects are not a problem because participants only do the experiment once (no practice effect)

Weakness of an independent measures design

- different participants in each group
- participant variables can act as EVs (reduces validity)

Matched Pairs Design

- pairs of participants are matched in terms of the variable relevant to the study, such as age or IQ. One member of each pair takes part in condition A of the experiment and the other takes part in condition B

Strengths of a matched pairs design

- no order effects (because they are only tested once)
- fewer participant variables

Weakness of a matched pairs design

- takes time to match participants
- doesn't control all participant variables

Repeated Measures Design

- when all the participants take part in all conditions of the experiment

Strengths of a repeated measures design

- no participant variables
- fewer participants needed, so less expensive

Weakness of a repeated measures design

- order effects reduce validity, e.g. practice effect

Counterbalancing

- where half of the total number of participants will take part in Condition A first, followed by Condition B and the pther half of participants will take part in reverse order (Condition B and then Condition A)

Ways of dealing with participant variables

- allocation to conditions: using chance or systematic method to allocate participants to conditions
- random allocation: ensures that each participant has an equal chance of being in one group as any other

Random Sampling

- each person has an equal chance of selection
E.g. numbers of a target population in a hat/ random generator

Strength of random sampling

- no bias as everyone has an equal chance of selection

Weakness of random sampling

- takes time as need a list of all the members of a target population

Oppurtunity Sampling

- the researcher selects people who happen to be there at that time

Strength of opputunity sampling

- quick and therefore cheap because participants there already

Weakness of oppurtunity sampling

- only represents the population from which it was drawn

Systematic Sampling

- a numerical formula is used, such as selecting every 50th name from the phonebook

Strength of systematic sampling

- avoids researcher bias (the researcher has no say over who is selected)

Weakness of systematic sampling

- may end up with an unrepresentative sample (a sample of low validity)

Stratisfied Sampling

- participants are selected from different subgroups in the target population in proportion to the subgroup's frequency in that population

Strength of stratisfied sampling

- most representative method

Weakness of stratisfied sampling

- very time-consuming to sort sub-groups
- the decision abt which subgroups to use may be biased (which reduces the representiveness)

Correlations

- mathematical technique used to investigate the relationship between two co-variables

Positive Correlation

- when one co-variable increases, the other also increases (and vise versa)

Negative Correlation

- when one co-variable increases and the other decreases

No Correlation

- when there is no relationship between co-variables

Strength of correlations

- good starting point for research
- they can be used to investigate more complex relationships (curvilinear relationships)

Weakness of correlations

- they can tell us that two co-variables are related but don't tell us how they are related
- intervening variables may be overlooked

Observations

- a research method where a researcher observes and recors a participant's behavior to see how they will respond in a given situation

Naturalistic Observation

- behavior is recorded the place where it will normally occur and nothing is changed in the environment

Controlled Observation

- the researcher controls some aspects of the situaion/ environment

Covert Observation

- when participants are not aware that their behavior is being recorded

Overt Observation

- participants are told in advance that their behavior will be watched and recorded

Participant Observation

- where the researcher takes part in the event being observed

Non-participant Observation

- the researcher remains seperate from the people they are studying

Strength of Observations

- provides better indication of behavior than questionniares/ interviews ---> high validity
- look at real-life behavior

Weakness of Observations

- Ethical issues
- observers have expectations of what the result could be - this could influence what they see/hear

Interobserver reliabiltiy

- the extent to which there is an agreement between two or more observers involved in an observation of behavior

Catergories of behavior

- when a target behavior is broken down into units that can be observed and recorded

Ethical issue

- when there is a conflict between the rights of participants to be safe and the goals of research to produce valuable data

Informed Consent

- where participants must be given comprehensive information about the goal and nature of the research and their goal in it for them to make an informed decision about whether to participate

Deception

- where the participant is not told the true aims of/ given false information about the study and cannot truly give their informed consent
- mild deception can be excused if the benefits of the results outweigh the costs of the deception

Protection from harm

- where participants should not be placed at risk, and their physical and psychological safety should be protected at all costs

Privacy

- where people expect to be able to control information about themselves

Confidentiality

- when a person's privacy has been invaded, their identity should be protected

Dealing with Informed Consent

- (before the study) a consent form that explains what is involved in the study and what the aims of the study are
- they should be asked to sign a consent form (participants under 16 will have their guardians sign this form)

Dealing with Deception and Protection from Harm

- (after the study) researchers should produce a letter for participants explaining the true aims of the experiment, that there were other participants involved, the fact that they have the right to withhold any data, and that all of their behavior was normal (debriefing)
- the participants should also know that if they feel uncomfortable at any point during the study, the investigation will be halted

Dealing with privacy and confidentiality

- all participants should remain anonymous
- psychologists should not share data with other researchers unless cleared by the participants in advance
- participants should be reminded that their data will be protected and remain confidential

Structured Interview

- where the interviewer reads out a list of prepared questions to the interviewee

Unstructured Interview

- more like a conversation
- the interviewer starts off with a general aim and lets the interviewee's answers guide the subsequent questions

Semi-structured Interview

- where a number of questions are already prepared in advance but the interviewer will ask follow up questions at certain points

Strength of interviews

- they produce extensive information
- they are the only way to obtain information from people who can't write or find it difficult to express their feelings on paper

Weakness of interviews

- data might be difficult to analyse
- people may feel less comfortable about revealing personal information

Questionnaire

- a set of written questions used to find out a person's thoughts or attitudes on a particular topic

Open Question

- does not have a fixed range of possible answers

Closed Question

- has a fixed range of answers

Strength of a questionnaire

- gather information from lots of people relatively quickly
- produce data that is often easier to analyse than interviews

Weakness of questionnaires

- respondants might not always answer truthfully
- questions might be unnclear or might be leading questions

Case Study

- an in-depth investigation of something which could be a single individual, a group, an event, or an institution

Strength of a case study

- researchers are often more open-minded when conducting a case study
- they are the best way of studying unusual behavior

Weakness of a case study

- often concern unique people or events
- subjective: based on the researcher's own reading and understanding of the case

Mean

- mathematical average of scores