| Sections in SELF REPORT (results) | - Abstract (brief summary)
- Introduction (background of research)
- Method (type of experiment + process)
- Results (descriptive stats + inferential stats)
- Discussion
- References
- Appendices |
| Random sample definition | - Individuals randomly selected to represent an entire group
- When everyone in the target population has an equal chance of being chosen |
| Strengths and weaknesses of random sampling | - No sampling bias
- Time consuming and difficult |
| Opportunity sample definition | - People who are conveniently around when doing the investigation |
| Strengths and weaknesses of opportunity sampling | - Very convenient method
- Bias, not representative |
| Target population definition | - The focus on the participants in the investigation |
| Self selected sampling definition | - Individuals choosing to take part in the investigation |
| Strengths and weaknesses of self selected sampling | - Very convenient method
- Bias, not representative |
| Snowball sampling definition | - A recruitment technique where participants are asked to choose other subjects |
| Strengths and weaknesses of snowball sampling | - Very convenient method
- Bias, not representative |
| Why use a mean? | - Everyone's scores are counted |
| Why use a median? | - Better when there is an anomaly as it doesn't get counted in final answer |
| Why use a mode? | - Easiest when all the scores are close together |
| How to write a hypothesis | - Clear statement
- IV + DV clearly stated |
| What is a null hypothesis | - Written alongside the main hypothesis to complete the prediction |
| How to write a null hypothesis | - There will be no significant difference between scores on condition A and B
- Any difference is down to chance |
| IV definition | - Variable that you manipulate |
| DV definition | - Variable that you measure |
| How can you self-report | - Interview
- Questionnaire
- Surveys
- IQ/personality tests
- Psychometric tests |
| Open questions | - Multiple answers
- Freedom to give answer without limiting response
- Qualitative data
E.g why do you like going to college? |
| Closed questions | - Could be multiple choice - or yes or no
- Very limited options/answers
- Quantitative data
E.g how did you get to college today?
bus
walk
train |
| Rating scales | - Likert rating scale
- Semantic differential rating scale |
| Likert rating scale | - strongly agree, agree, neither, disagree, strongly disagree (statement and 5 options on how they feel about statement) |
| Semantic differential rating scale | - Give line, word on each end e.g. happy/sad
Sad —------------------------------X----------------------- Happy |
| Designing a questionnaire survey | - Use closed questions + open questions
- Keep questions and instructions clear and easy to understand
- Carry out a pilot study first |
| Strengths of questionnaires | - Quick
- Can collect large amounts of data
- Convenient - researcher does not need to be present |
| Weaknesses of questionnaires | - Social desirability - people say what they think looks good
- People may not tell the truth
- Postal surveys may have low response rate
- Difficult to phrase questions clearly, you may get different interpretations |
| Different types of interviews | - Unstructured
- Structured
- Semi-structured |
| Unstructured interviews | - No fixed questions
- Conversation
- Recorded, video or audio, give consent
- Usually qualitative data
- Not limited
- Highly relies on skilled interviewer |
| Structured interviews | - Fixed set of questions
- Same questions for everyone
- Usually quantitive data
- Limited |
| Semi-structured interviews | - Set of questions but allow interviewee to expand their answers
- Quantitive + qualitative |
| Advantages to interviews compared to questionnaires | - Allows you to rephrase the question if the person doesn't understand it
- Get data straight away, practical
- Can be flexiable |
| Disadvantages to interviews compared to questionnaires | - Demand characteristics in interviews, social desirability bias
- Questionnaires are less stressful, no pressure if done alone |
| Validity | - The extent to which a measure measures what it is supposed to measure |
| EXTERNAL validity | - Whether the results can be generalised if conducted in a different place, time or with different Ps |
| Three types of external validity | - Population
- Ecological
- Temporal |
| Population Validity | - Whether the findings from the study can be generalised to the target population, or to different groups of people |
| Ecological Validity | - Whether a test measures behaviour that is representative of naturally occurring behaviour |
| Face Validity | - Does the test look like it measures what it intends to measure? |
| Temporal validity | - Can results be applied to other historical times? |
| INTERNAL validity | - Extent to which a measurement technique measures what it is supposed to measure
- Whether the IV really caused the effect on the DV or whether some other factor was responsible |
| Three types of internal validity | - Construct
- Concurrent
- Criterion |
| Construct Validity | - Does the test measure all aspects of the behaviour? |
| Concurrent Validity | - Comparing current study/test with previously validated study / test of the same nature |
| Criterion Validity | - Can the study/questionnaire predict future behaviour or attitudes? |
| Reliability | - Consistency
- The extent to which the findings can be repeated |
| Types of reliability | - Internal
- External |
| Internal Reliability | - Consistency of a measure |
| External Reliability | - Extent to which a measure is consistent when assessed over time or across different individuals |
| Laboratory experiments ADVANTAGES | - More control over the variables, increases reliability
- As u are more confident that the IV is the only factor influencing the dependent variable |
| Laboratory experiments DISADVANTAGES | - Demand characteristics
- Participants may be aware that they are participating in an experiment
- Behave differently to how they would typically behave, reducing validity |
| Field experiments ADVANTAGES | - High EV than lab, as the natural settings will relate to real life
- Demand characteristics are less of an issue than lab, people more likely to act naturally |
| Field experiments DISADVANTAGES | - Extraneous variables could effect results due to reduced control
- Ethical issues, like lack of informed consent
- Difficult to replicate, low reliability
- Sampling bias, ppts often not randomly allocated to conditions |
| Quasi experiments ADVANTAGES | - High ecological validity – lack of involvement of the researcher
- Variables naturally occurring, findings easily to generalise |
| Quasi experiments DISADVANTAGES | - Lack of control over extraneous variables, cannot always assess the effects of the IV, low internal validity
- Not replicable, lack of control, so reliability of results cannot be checked |
| Independent measures design ADVANTAGES | - Reduces demand characteristics, ppts only take part in one condition they are less likely to pick up on clues + cues, high internal validity
- Reduces order effects, ppts are only tested in one condition so they will not improve through practise or become bored through repetition, high internal validity |
| Independent measures design DISADVANTAGES | - Requires more ppts, expensive
- Participant variables as different ppts are being used in each condition
- This means that the IV isn’t the only variable to change across the different conditions and therefore a cause and effect relationship cannot be established |
| Repeated measures design ADVANTAGES | - Less ppts required because the same ppts used in all of the conditions, cheap
- Reduces ppt variables as same ppts are being used in each condition
- This means that ppt variables are kept consistent, providing all other EVs are controlled this means that the only IV changes across the conditions |
| Repeated measures design DISADVANTAGES | - Order effects as ppts take part in all the conditions, more likely to become bored or practiced, measuring unnatural behaviour, lowering internal validity
- Demand characteristics, ppts taking part in each condition can help them to guess the aim of the study and therefore change their behaviour, so researcher is not measuring what they intend to measure, low internal validity |
| Matched pairs design ADVANTAGES | - Reduces demand characteristics, ppts only take part in one condition they are less likely to pick up on clues + cues, high internal validity
- Reduces order effects, ppts are only tested in one condition so they will not improve through practise or become bored through repetition, high internal validity |
| Matched pairs design DISADVANTAGES | - Requires more ppts, expensive
- Participant variables as different ppts are being used in each condition
- This means that the IV isn’t the only variable to change across the different conditions and therefore a cause and effect relationship cannot be established |
