1. Questionnaires- Advantages
They are highly replicable, as the questions are standardised, meaning the findings can be checked for reliability.
They are time, and cost effective, as someone isn’t required to ask the questions, meaning a large amount of data can be collected.

2. Questionnaires- Disadvantages + ethical issue
Individuals may answer the questions, in a way to make them seem socially desirable leading, which limits the validity of the findings.
Researchers aren’t always there to help so if people don’t understand the questions then they may just leave them blank- makes the data harder to analyse.
Issue of confidentiality- people may not want others sharing the information they have given if its particularly sensitive.- overcome by asking permission before hand.

3. Unstructured/ structured questionnaries/ interviews
In structured interviews the questions are pre- set so are easy to replicate
However in unstructured interviews the questions are developed based on the interviewees responses

4. Open vs closed questions
Open questions are ones which can’t be answered simply by a yes/know response eg. How do you feel- these provide more rich detail but are harder to analyse- eg. Different each time
Closed questions however are usually answered by a yes/no so are easier to analyse

5. Interviews- Advantages
Qualitative data can be gathered from interviews, as open questions can be asked, making the findings more useful.
They are more appropriate to use with sensitive issues, as the interviewer can gauge, if the participant is distressed.

6. Interviews- Disadvantages
They take time and money to conduct as someone has to be there to ask the questions, and open questions elicit more detailed responses.
Low inter-reliability between interviews of the same participant- due to interview effects of age-gender- elicit different responses from individual- ask different questions.
Social desirability bias- validity of findings.

7. Case studies
Unique cases can challenge existing beliefs leading to the development of new theories.
They enable researchers to investigate topics which would typically be impractical/ unethical to investigate in a lab setting
Generally longitudinal and can show the complex interaction between many factors, in contrast to experiment

8. Case studies - Disadvantage
Only a small number of individuals are studied, meaning the results can’t be generalised to the entire population.
Ethical issues- young participants/ those with a disorder.
Typically rely on recollection of past events – such evidence may be unreliable

9. Observational techniques
In order to information easier to collect when observing behaviour, psychologists use behavioural categories.
Also sampling methods such as time sampling and event sampling may be used.
These structured techniques enable psychologists to study behaviour more easily.

10. Observations - Advantages
High ecological validity- ppts unaware of observation, then behaviour is natural.
Allow researchers to investigate topics that would be impractical/unethical to investigate using experiments

11. Observations- Disadvantages + ethical issue
Hawthorne effect- participants aware of observation- they will adjust their behaviour accordingly – low ecological validity
Low reliability- observational bias- draw incorrect conclusions from different behaviour
Ethical issue- fully informed consent and right to withdraw.

12. Correlational analysis- Advantages
Precise method- tells researches the strength and relationship between two variables
Frequently use pre-existing data- ppts/facilities aren’t required, so time and cost effective.

13. Correlational analysis – disadvantages
Hard to establish cause and effect for certain between two variables, can be other variables which effect the outcome. ( intervening variables )
Can only measure linear relationships- not curvilinear relationships- where positive becomes negative

14. Experimental methods – Lab studies – Advantages
High internal validty – extraneous variables that can effect the dependent variable can be controlled – so cause and effect can be determined with reasonable confidence.
They are easily replicable- same methods can be used again- to check for reliability of findings

15. Lab studies – cons
Low ecological validity- simulated environment- artificial stimuli – behaviour doesn’t reflect real life.
Demand characteristics are likely- ppts will change their behaviour if they’re being watched- low validty

16. Field study – advantages
Ecological validity is higher than a lab- findings can be generalised
Demand characteristics are lower than a lab study, as ppts are aware taking part in a study so act more naturally.

17. Field study- cons
Extraneous variables that can effect the dependent variable are more difficult to control than with a lab study- lower validty
The sample used may not represent the entire population- population validity is reduced

18. Natural study - pros
Demand characteristics are greatly reduced if ppts aren’t aware they’re taking part in the study- behave more naturally.
High ecologically validity- natural environment with naturally occurring independent variable

19. Natural study- Cons
Extraneous variables can’t be controlled- limited the validity of the results
Ethical issues- right to withdraw and confidentiality may be breached if participants are unaware they’re in a study

20. Independent groups - Pros
Order effects such as tiredness and boredom are reduced as participants are only experiencing one condition – more valid results
Each participant only takes part once so only one set of stimulus materials needs to be produced- making the test fairer

21. Independent groups- cons
More participants are required so it is more expensive + time consuming to organise
Individual differences between the participants may have an adverse effect on the results and subsequent conclusions.

22. Repeated measures- pros
Less participants are needed than with independent groups, as the same participants take part in each condition- so its cheaper
Results from the same participants are shared, so individual differences won’t effect the results.

23. Repeated measures- cons
As participants take part in both condtions order effects such as tiredness and boredom can affect the results- reduce validity
Two sets of stimulus materials are required- which can create extraneous variables- if one task is more difficult than the other ect

24. Only one set of stimulus materials are used- makes the test fairer
Matched pairs – where participants take part in each condition but are matched based on key variables- Pros
Participants only experience one condition so order effects such as boredom are reduced- increasing validity.
Only one set of stimulus materials are used- makes the test fairer

25. Matched pairs - Cons
Difficult and time consuming to match people on certain characteristics- may not be accurate
If one person from a pair doesn’t want to participate, then data from the pair Is lost – not cost effective

26. Aims +Hypothesis – Directional and non- Directional
Aims of an experiment – what the researcher intends to study
Directional hypothesis – state the type of relationship between two variables- one variable will cause another to increase
Non- directional hypothesis – simply state that one variable will have an effect on another but don’t know which direction this will act in
Null Hypothesis- independent variable won’t have an effect on the dependent variable

27. Variables – IV/DV/ Extraneous variable
Iv- The variable that you change
Dv- variable that you measure
Extraneous variable – Variable other than the Iv, that may have an effect on the dv.

28. 4 extraneous variables
Participant variables – Differences between ppts such as age, personaity, intelligence gender- Use repeated measures
Situational variables – Features of the research environment – time of day, temperature, noise, stimulus material used. – standardise the study
Demand characteristics- Clues in the research environment- tasks ect that will help ppts know what hypothesis is- change their behaviour accordingly
Investigator effects- Characteristics of the researcher that might affect the way ppts act- age gender

29. Purpose of pilot studies
Small scale pilot study used- test the methods of the study – instructions to ppts/ instructions given.
Highlight issues and rectify them- without wasting lots of ppts + money

30. Population + representativeness
Population refers to all the people who the researcher wishes to make a statement about.
The aim is to select a representative sample from this target population who represent the target population eg. IQ,Age, race, sex
Representativeness is important so that the findings of the study can be generalised to the target population.

31. Mean
It is the average value of set of observations. Sum, divided by the number of them.
Pros – Uses all the data, is the centrepoint
Cons- anomalies mean it can be skewed- not always an integer value

32. Median
Middle score of a set of observations when they are written in order
Not affected by extreme values in data set
Quick and easy to calculate
Not useful with fata sets with large differences, or not many observations

33. Mode Most common score in a data set
Not affected by extreme values – lies in data set
May not be only one mode
Doesn’t include all the data

34. Range Easy to calculate Takes into account extreme values
Affected by extreme values
Unlike sd, it doesn’t show the true devition from the mean

35. Standard deviation + what it shows
How much observations deviate from the mean
Large sd = ppts answered very differently as lot f variation around the mean scores spread widely
Small deviation – scores closely clustered around the mean – ppts answering in very similar way
Difficult to calculate
Detailed conclusion
Precise as uses al values

36. The major features of science
Science (from Latin scientia, meaning "knowledge") is a branch of knowledge gained from careful and systematic investigation which is used to predict general laws.
Psychology follows the principles of other sciences, such as biology and chemistry.
These include:
Replicability
Objectivity
Theory construction
Hypothesis testing
The use of empirical methods
These features are named on the specification so you could be asked a question specifically about each one.

37. Replicability/empirical methods/ objectivity/ theory construction/hypothesis testing is an important part of the scientific process. Scientific method involves defining a problem and formulating a hypothesis which is tested with empirical research.

38. The use of empirical methods
Replicability/empirical methods/ objectivity/ theory construction/hypothesis testing is an important part of the scientific process. Scientific method involves defining a problem and formulating a hypothesis which is tested with empirical research.
The word empirical means information gained by experience, observation, or experiment, rather than by reasoned argument or unfounded belief.
The central theme in the scientific method is that all evidence must be empirical which means it is based on evidence.
This is important because people can make claims about anything but the only way we know if such things are true is through direct testing i.e. empirical evidence.

39. Replicability
Replicability/empirical methods/ objectivity/ theory construction/hypothesis testing is an important part of the scientific process. Scientific method involves defining a problem and formulating a hypothesis which is tested with empirical research.
If we can carry out research again at another time and find the same or similar findings, we can say that our findings are replicable.
This is why it is important that our method is carefully controlled and reported (including operationalisation of variables in an experiment).
It is only by replicating research that we can be sure that our findings are valid and reliable.
Unrepeatable results may imply flaws or lack of control within the method used and are of limited use in theory construction.

40. Objectivity
Scientists strive to be objective in their observations and measurements.
This means that they try not to let their own opinions and expectations affect what they record.
In order to be objective the ideal is to carefully control conditions in which research is conducted.
This is important because it means that the experiment should get the same result regardless of who it is carried out by.

41. Theory construction
Theories are constructed using the scientific process.
Hypotheses are developed based on observation of phenomena.
These hypotheses are then rigorously tested.
A hypothesis that is consistently supported leads to the development of a theory.
Observation
Develop hypothesis
Test hypothesis
Hypothesis
is supported
Hypothesis is
not supported
Develop
theory
Develop new
hypothesis

42. Hypothesis testing
The scientific method progresses by hypothesis testing.
Our hypothesis might be that people are happier in the summer. We must then do our best to test this hypothesis.
We must try everything we can to disprove (falsify) our hypothesis. If we cannot find evidence to do this, we can accept our hypothesis.

43. Validating new knowledge and the role of peer review
Peer review is the assessment of scientific work by others who are experts in the field. The intention of peer reviewing is to ensure that any research conducted and published is of high quality.

44. Problems with peer review
Unachievable ideal – it isn’t always possible to find an appropriate expert to review a research proposal or report. This means that poor research may be passed because the reviewer didn’t really understand it.
Publication bias – peer review tends to favour the publication of positive results, possibly because editors want research that has important implications in order to increase the standing of their journal.
Biased reviewers – as the research is in the reviewers area of expertise, it may cite the reviewer’s own work. This could mean that they are less likely to approve work that does not agree with their own.

45. Peer review is important because….
provides a way of checking the validity of the research and making a judgment about the credibility of the research and the appropriateness of design and methodology
Peers can judge the significance of the research in the wider context
Peers can assess how relevant research is
Peers can make a recommendation on where the research paper should be published in its original form or if it should be revised in some way.
Peer review process ensures any research published in well-respected journal has integrity and can be taken seriously by fellow researchers

46. Opportunity sample
Participants are selected using those people who are most easily available. This is the easiest and cheapest method to use, but it is inevitably biased because the sample is drawn from a small part of the target population.
For example, if you selected your sample from people walking around the centre of a town on a Monday morning, it would be unlikely to include professional people (because they are at work).

47. Volunteer sample
Participants are selected by asking for volunteers. For example, placing an advertisement on a college notice board. This method can access a variety of participants if the advertisement is, for example, in a national newspaper, which could make the sample representative.
However, such samples are inevitably biased because participants are highly motivated and/or with time on their hands.

48. Random sample
Participants are selected using a random number technique. First, all members of the target population are identified (e.g. all the members of one schools or all the members of a town) and then individuals are selected either by the lottery methods (numbers chosen from a hat) or a random number generator.
This method is potentially unbiased because all members of the target population have an equal chance of selection, though in the end a researcher may still end up with a biased sample because some people refuse to take part.

49. Types of reliability
Reliability refers to how consistent a study or measuring device is. A measurement is said to be reliable or consistent if the measurement can produce similar results if used again in similar circumstances.
Internal reliability - Internal reliability refers to the extent to which a measure is consistent within itself (e.g. whether all questions on a questionnaire are measuring the same thing).
External reliability - External reliability refers to the extent to which a measure varies from one use to another.
Inter rater reliability –The extent to which two or more raters agree.

50. Assessment of reliability
Test retest – repeat the test on different occasions to see if it produces the same results.
Split half – split the instrument in half (e.g. a questionnaire) and compare the two halves to see if results are similar.
Inter rater – a statistical test (Spearmans) can be used to check the degree of agreement (correlation) between raters.

51. Improving reliability
Improving internal reliability – the researcher can remove items (e.g. questions on a questionnaire) individually until the unreliable items are identified.
Improving external reliability – individual aspects of the study can be checked to identify the unreliable factors e.g. if the same instructions were given to participants each time the research was repeated.
Improving inter rater reliability – ensure that clear behavioural categories are identified, and that all observers are fully trained on how to apply them.

52. Types of validity
Internal validity is the extent to which the research measures what it intends to.
External validity is the extent to which the results of the research can be generalised. External validity can be further divided into:
Ecological validity – the extent to which results can be generalised settings other than the one it was carried out in.
Population validity – the extent to which results can be generalised to people other than the participants it was carried out on.

53. Assessing validity
Concurrent validity is a way of assessing validity by comparing the results with another measure. For example, we could compare the results of an IQ test with school results. If the other measure is roughly compared at the same time we call this concurrent validity.
Ask an expert(s) in the field to assess the questions to see if they are an accurate measure of what its supposed to measure(content validity)
Construct validity is a way of assessing validity by investigating if the measure really is measuring the theoretical construct it is suppose to be. For example, many theories of intelligence see intelligence as comprising a number of different skills and therefore to have construct validity an IQ test would have to test these different skills.

54. Improving validity
Internal validity can be improved by careful operationalisation of variables and control of extraneous variables, including demand characteristics and investigator effects.
Population validity can be improved by careful selection of participants.
Ecological validity can be improved by carrying out research in natural environments.

55. BPS ethical guidelines
Protection of participants – P’s should experience no more distress than is likely in every day life.
Confidentiality – Data must be stored securely and identifying details should be removed.
Informed consent – P’s should be given enough information to be able to decide whether they want to take part.
Deception – Where possible, P’s should not be deceived about the purpose of the study.
Right to withdraw – P’s should be able to withdraw themselves and their data from the study at any time.
Debrief – P’s should be told the purpose of the study when it is complete, and be given the opportunity to ask questions. They may also be given advice/offered counselling if appropriate. A full debrief is particularly important if P’s have been deceived as to the purpose of the study.

56. Dealing with ethical issues
An ethical issue occurs when there is a dilemma between what the researcher wants to do and the rights and dignity of the participants.
Some ways that ethical issues can be dealt with are:
Debriefing can deal with a lot of ethical issues such as deception and protection of participants.
Informed consent for children (under 16) can be gained from parents.
Prior general consent can be gained to deal with deception and informed consent (agreeing to take part in a study but not being fully aware of the details/aims of the research.

57. Type 1/Type 2 errors
A Type 1 error is a false positive. It occurs when we accept the experimental hypothesis as significant when it is not (thus rejecting the null hypothesis).
A Type 2 error is a false negative. It occurs when we reject the experimental hypothesis (and accept the null hypothesis) when it is in fact significant.
The chance of Type 1/2 errors is associated with the significance level (P value) we use. If we use a 1% level, the chance of a Type 2 error is increased, whereas a Type 1 error is more likely when a 10% significance level is used.

58. Factors affecting choice of statistical test
When choosing a test you will need to be able answer 3 questions:
The level of measurement of the data – nominal, ordinal or interval/ratio.
Whether you are looking for a difference or association.
The experimental design used - whether you are using an independent groups design or not.

59. Levels of measurement
Nominal data is category data, e.g. whether participants are stressed or not. There can be no overlap – they are either in one category or another.
Ordinal data is data that is ranked in order, but with no meaningful difference between them. This might be used to rank P’s in order of how stressed they are.
Interval/ratio data is measured on a scale. This would be used when participants are given a score on a stress test.

60. Factors affecting choice of statistical test
Difference or association – are you looking for a difference between two groups e.g. stress levels of doctors and teachers or an association e.g. stress levels and annual pay?
Experimental design – are you using an independent groups design? For the purposes of choosing a test, a matched pairs design is treated in the same way as a repeated measures design (i.e. not as two separate groups).

61. The use of inferential statistics
Calculate the observed value.
Consult the appropriate critical values table and find the relevant critical value using the following steps:
Select whether a one or two tailed test is to be used.
Select the appropriate level of significance.
Calculate degrees of freedom (for chi square).
Identify the number of participants (for Spearmans and Wilcoxon – shown as N)
For Mann Whitney, you will need to know the number of participants in each group (shown as N1 and N2).

62. Chi square
Used with nominal data.
Can be used for a difference or association.
Needs a minimum of 20 participants.
Data should be plotted in a contingency table.
Degrees of freedom (DF) should be calculated by multiplying the number of rows in the contingency table, minus one, by the number of columns, minus one.
Male
Female
Totals
Sleep
≥ 8 hours 5 12 17
< 8 hours 10 9 29 15 21 36
However, in the exam, you will always be provided with the figure for degrees of freedom.

63. Spearman’s Rho Used when:
A hypothesis predicts a correlation between 2 co-variables.
When 2 sets of data are pairs of scores from one person, e.g. hair colour & IQ score.
The data are ordinal or interval, i.e. NOT nominal.

64. Mann Whitney Used when:
The hypothesis predicts a difference between 2 sets of data.
The 2 sets of data are from separate groups of pp’s – independent groups.
The data needs to be ordinal or interval – NOT nominal.

65. Wilcoxon
Used when:
The hypothesis predicts a difference between 2 sets of data.
The 2 sets of data are pairs of scores from one person – repeated measures/matched pairs.
The data needs to be ordinal or interval – NOT nominal.

66. Reporting your results
You should state:
The observed value
The critical value
The probability value (e.g. p<0.05)
The type of test used (e.g. Chi square)
The degrees of freedom (df) for Chi square
The number of participants
Whether you accept/reject the alternative/null hypothesis
Whether or not the result is significant

67. Analysis and interpretation of qualitative data
Qualitative data involved people’s meanings, experiences and descriptions. It is particularly good for researching attitudes, opinions and beliefs.
Data usually consists of verbal or written descriptions.
Most qualitative methods look for common themes within the data.
These may be illustrated with the use of direct quotes.

68. Content analysis
Content analysis is a very simple form of analysing qualitative data by converting it into a quantitative form by counting themes within the data.
Identify the material to be studied (e.g. interviews, adverts, etc.)
Identify coding units.
Count the number of times that each theme occurs in the data.

69. Evaluation of content analysis
STRENGTHS
A very simple and relatively quick method of analysing qualitative data.
LIMITATIONS
Some of the detail and richness of the data may be lost in converting to qualitative categories.
The research could be biased in their interpretation of the data – this can be reduced by having several raters and checking for inter-rater reliability.

70. Conventions of reporting on psychological investigations
Abstract – a very brief summary of the study covering the aims/hypothesis, method/procedures, results and conclusions.
Introduction – this usually includes a review of past research in the area, and an explanation of why the current research is being carried out. The research aim and/or hypothesis will usually be included in the introduction too.

71. Method – a detailed description of what the researchers did, providing enough information to replicate the study. This section is often broken down to include:
Design – an overview of the study, including justification for design decisions (e.g. why a field experiment was used rather than a lab experiment). Ethical issues may also be addressed here.
Participants – the sample size and other important information (e.g. gender, ethnicity, etc where relevant). The sampling and recruitment method should also be included.
Apparatus/materials – equipment used, such as standardised instructions, computer programs, questionnaires, interview schedules, etc.
Procedure – a step by step description of how the study was carried out.

72. Results – this section contains what the researchers found
Results – this section contains what the researchers found. It may include descriptive and inferential statistics.
Discussion – the researchers offer explanations for the behaviours they observed and might also consider the implications of the results and make suggestions for future research.
References – the full details of any sources that have been used in the report (books, journals and websites).
Appendix – anything that is important to the report but does not fit in the main body of the report e.g. raw data, copies of interview schedules, questionnaires, etc.

73. Report writing
As part of the report writing process, you will also need to be able to write:
Consent form – giving enough information for P’s to make an informed decision about taking part in the research.
Debrief – informing participants of the full nature of the research and offering the opportunity to ask questions.
Standardised instructions – given/read to P’s to ensure consistency/control extraneous variables.