AQA A Level Psychology Topic Companion · AQA A LEVEL Psychology topic companion: RESEARCH METHODS Page 5 A strength of using natural experiments is the unique insights gained into

Joseph Sparks & Helen Lakin

AQA A Level Psychology

Topic CompanionResearch Methods

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Contents

Page 2 AQA A LEVEL Psychology topic companion: RESEARCH METHODS

TopicExperimental Methods 3

Observational Techniques 8

Self-Report Techniques 15

Correlations 20

Case Studies [A-Level Only] 23

Aims, Hypotheses, IVs And DVs 25

Sampling 28

Pilot Studies and Experimental Design 34

Control, Demand Characteristics, and Investigator Effects 38

Ethical Guidelines, Peer Review and The Economy 41

Types of Data 47

Descriptive Statistics 50

Presentation and Display of Quantitative Data 57

Distributions: Normal and Skewed Distributions 59

Content Analysis [A-Level Only] 60

Features of Science [A-Level Only] 63

Reliability [A-Level Only] 66

Validity [A-Level Only] 69

Reporting Psychological Investigations [A-Level Only] 72

The Sign Test [As And A-Level] 77

Levels of Measurement [A-Level Only] 80

Probability and Significance [A-Level Only] 83

Statistical Tests [A-Level Only] 85

Appendices 90

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AQA A LEVEL Psychology topic companion: RESEARCH METHODS Page 3

EXPERIMENTAL METHODS Specification: Experimental method. Types of experiment: laboratory and field experiments; natural and quasi experiments. WHAT YOU NEED TO KNOW Outline and evaluate laboratory experiments. Outline and evaluate field experiments. Outline and evaluate natural experiments. Outline and evaluate quasi experiments. Introduction Experimental methods all have one thing in common: they are attempting to find a cause and effect relationship between an independent variable (IV) and dependent variable (DV), and to measure the extent of this effect. There are four different types of experiment:

1. Laboratory experiment 2. Field experiment 3. Natural experiment 4. Quasi experiment

Summary of Experimental Methods SETTING IV DV

LABORATORY Controlled conditions Manipulates the IV Measures the DV

FIELD Natural conditions Manipulates the IV Measures the DV

NATURAL Natural conditions IV is naturally occurring (e.g. unemployment and an earthquake)

Measures the DV

QUASI Controlled conditions /Natural conditions

IV is a difference between people (e.g. gender and age)

Measures the DV

Laboratory Experiments Laboratory experiments are conducted under specified controlled conditions in which the researcher manipulates the independent variable (IV) to measure the effect on the dependent variable (DV). The conditions are heavily controlled in order to minimise the effect of any extraneous variables, to prevent them from becoming a confounding variable which might adversely affect the DV. Participants will be aware that they are taking part in an investigation due to the contrived nature of the situation which may feel unlike real‐life.

AQA A LEVEL Psychology topic companion: RESEARCH METHODS


Evaluating Laboratory Experiments A strength of laboratory experiments is the high degree of control over extraneous variables which can

be achieved. A researcher is therefore able, in most cases, to prevent extraneous variables from becoming confounding variables which negatively affect the DV. This provides a high degree of internal validity allowing for conclusions about cause and effect to be drawn between the IV and DV.

A limitation of laboratory experiments is that they can lack external validity. The artificial nature of the

environment in which the investigation is taking place means that the study can lack ecological validity. This means that the findings of the study cannot always be generalised to settings beyond the laboratory as the tasks often lack mundane realism and would not be everyday life occurrences. Since participants know they are being investigated their behaviour can also change in an unnatural manner resulting in demand characteristics being seen.

Field Experiments Field experiments are carried out in natural conditions, in which the researcher manipulates the independent variable (IV) to measure the effect on the dependent variable (DV). The ‘field’ is considered any location which is not a laboratory. Participants in a field experiment typically do not know that they are taking part in an investigation with a view to observing more natural behaviour. Evaluating Field Experiments The natural setting means that field experiments often have a higher level of ecological validity, in

comparison to laboratory studies. This means that the results are more likely to be representative of behaviour witnessed in everyday life. However, because the setting is more natural, there is less control over extraneous variables. These can then become confounding variables and distort the findings meaning a firm cause and effect relationship cannot be drawn since other factors could have had an impact on the DV, other than the IV.

There are important ethical issues associated with field experiments. Since participants are often

unaware that they are in fact participants in a psychological investigation, they cannot give informed consent to take part. As such, the research may involve a breach of their privacy rights and a cost‐benefit analysis will need to be conducted before proceeding with any study to ensure the perceived outcomes from the research will outweigh any personal costs to those involved.

Natural Experiments In a natural experiment, the researcher does not manipulate the IV and instead examines the effect of an existing IV on the dependent variable (DV). This IV is naturally occurring, such as a flood or earthquake, and the behaviour of people affected is either compared to their own behaviour beforehand, when possible, or with a control group who have not encountered the IV. It is important to note that it is the IV which is natural in this type of experiment, and not necessarily the context in which the investigation is taking place since participants could be tested in a laboratory as part of the study. Evaluating Natural Experiments The naturally occurring IV means that natural experiments often have a higher level of external validity

compared to laboratory and field experiments. These types of investigations are considered high in ecological validity given the real‐life issues that are being studied rather than manipulated artificially. However, natural experiments have no control over the environment and subsequent extraneous variables, which means that it is difficult for the research to accurately assess the effects of the IV on the DV. It may be that a confounding variable has affected the results so a cause and effect relationship must be drawn with extreme caution, if at all.



A strength of using natural experiments is the unique insights gained into real‐life situations from using this methodology. Investigating a naturally occurring IV allows for research to be conducted into areas of psychology that could not be generated for ethical reasons or because of logistical and practical constraints. However, a naturally occurring event that interests researchers may only occur very rarely. This limits the opportunity to generalise the results to other similar events or circumstances.

Quasi Experiments Quasi experiments also contain a naturally occurring independent variable (IV), but one which already exists. However, in this instance the IV is a difference between people such as gender, age or a personality trait. The researcher examines the effect of this IV on the dependent variable (DV). Quasi experiments do not have to be conducted in a natural setting, although they often are. They may also be conducted in a laboratory setting, under controlled conditions. Evaluating Quasi Experiments A limitation of quasi experiments is that participants cannot be randomly allocated to research

conditions to remove the issue of bias in the procedure. Since the IV is a naturally occurring difference between the participants, the level of IV to which they belong is predecided. This means the psychologist will be less certain that the IV alone will have caused the effect which is measured through the DV as other dispositional or environmental factors may have played a role in the outcome. That being said, quasi experiments allow researchers to compare different types of people easily to provide insight into similarities or differences between these groups which could not be ethically generated otherwise.

There are methodological issues associated with conducting quasi experiments. When quasi

experiments take place under natural conditions, there is no control over the environment and subsequent extraneous variables, making it difficult to be sure that factors such as age, gender or ethnicity have affected the DV. On the other hand, when quasi experiments take place under laboratory conditions the high level of control means that the research often lacks ecological validity, and the findings cannot always be generalised to a real‐life setting since behaviour may not translate outside of the research environment.

Comparison of Experimental Methods ECOLOGICAL VALIDITY EXTRANEOUS VARIABLES REPLICABILITY LABORATORY Low Controlled High

FIELD High Not controlled Low

NATURAL High Not controlled Low

QUASI *Low/High *Controlled/Not controlled *High/Low *The level of each factor depends on whether the quasi experiments are carried out in a laboratory setting or under natural conditions. Possible Exam Questions 1. Dr Helpful was interested in studying expectations when meeting a new work colleague for the first

time. Each participant who volunteered to take part was taken to the same room where they listened to a description of their new potential work mate called ‘Ms B’. The participants were randomly allocated to one of two groups in the experiment. Dr Helpful gave each participant exactly the same background information about ‘Ms B’, but the order of the information varied depending the experimental condition as follows:



Group 1 Three strengths of Ms B’s CV were followed by three negative comments. Group 2 Three negative comments about Ms B’s CV were followed by three strengths. After listening to the excerpt from Ms B’s CV, each participant was asked to state whether they thought Ms B would be a competent colleague to have on their work team or not. Dr Helpful recorded how many participants in each group stated that Ms B was ‘competent’. Identify which type of experiment that was conducted by Dr Helpful. (1 mark)

2. What is meant by the term ‘quasi experiment’? (2 marks) Exam Hint: It is important for students to remember that quasi experiments can be conducted in either a laboratory or a natural setting. 3. Identify two features of an experiment. (2 marks)

4. Outline what is meant by a laboratory experiment. (2 marks)

5. Identify and explain one difference between a laboratory and a field experiment. (2 marks) 6. A psychologist was interested in investigating whether people with phobias were more aware of their

own heartbeat than people who do not suffer with a specific phobia. A matched pairs design was adopted. The sample included eight individuals with a phobia and eight people without a phobia. The investigator asked each participant to make an estimation about how fast their heart was beating (in beats per minute). This figure was compared to their actual heartbeat measurement. Results showed that people with a phobia were more accurate at estimating their own heartbeat than people who did not suffer with a phobia at all.

Explain why this study is considered a quasi experiment. (2 marks)

Exam Hint: Many students often recognise that quasi experiments do not involve manipulation of the IV, but in questions like this can struggle to apply this understanding to the context of the question; that phobias could be pre‐existing (evolutionary/biological origin) or naturally occurring (learned from the environment). 7. Describe one difference between a natural experiment and a field experiment. (2 marks) 8. Donald, a middle‐aged male politician, approached an adult in a busy street and asked for directions to

the nearest bus stop. He repeated this with 14 other adults in the same city.

Each of the 15 adults asked were then approached by a second researcher, called Melania, who showed each of them six photographs of different middle‐aged politicians, including a photograph of Donald. Melania asked the 15 adults to choose the image of the individual who had asked them for directions to the bus stop. Melania estimated the age of each of the 15 adults and noted whether each participant had chosen the correct photograph of Donald. Suggest one reason why the researchers decided to use a field experiment rather than a laboratory experiment. (2 marks)

Exam Hint: Students can gain marks here for responses referring to the benefits in terms of validity or fewer demand characteristics but must elaborate their point fully to achieve the second mark.



9. What is meant by an extraneous variable? (2 marks) Exam Hint: Students need to avoid vague definitions of extraneous variables such as, ‘something that cannot be controlled’ or ‘something that must be controlled’. Answers must be specific by referring to the fact that an EV is a variable that is not manipulated by the experimenter but may have an effect on the dependent variable making it difficult to establish a cause and effect relationship.

10. Explain why it is important to control extraneous variables in experimental research. (2 marks) Exam Hint: Stronger answers to this question will refer to ‘confounding variables’ in their answer. 11. Eleanor was interested in investigating the impact of caffeine on memory.

Discuss advantages of carrying out an experiment like this in a laboratory. (4 marks)

Exam Hint: If students write about disadvantages here no marks will be awarded as the question clearly asks for ‘advantages’. Answers which refer to specific advantages (e.g. higher control of extraneous variables) and link it appropriately to the scenario (e.g. strength of caffeinated drink assured) will be able to access the full range of marks available. 12. Outline and evaluate the use of laboratory experiments in psychological research. Refer to specific

examples in your answer. (8 marks)


OBSERVATIONAL TECHNIQUES Specification: Observational techniques. Types of observation: naturalistic and controlled observation; covert and overt observation; participant and non‐participant observation. Observational design: behavioural categories; event sampling; time sampling. WHAT YOU NEED TO KNOW Outline and evaluate observational techniques, including:

o Covert and overt o Participant and non‐participant o Naturalistic and controlled o Structured and unstructured

Outline and evaluate the factors involved in the design of observational research, including: o Behavioural categories o Event sampling and time sampling

Introduction to Observational Techniques When conducting an observation, the researcher has the choice between: Covert and overt Participant and non‐participant Naturalistic and controlled Structured and unstructured

It is important to note that these techniques are not mutually exclusive: it is quite possible for an observation to be naturalistic, unstructured, participant and covert all at the same time, as these terms refer to different aspects of the methods. Covert Observations A covert observation is also known as ‘undisclosed’ observation and consists of observing people without their knowledge; for example, using a one‐way mirror (covert non‐participant) or joining a group as a member (covert participant). Participants may be informed of their involvement in the study after the observation has taken place. Evaluating Covert Observations A strength of covert observation compared to overt

observation is that investigator effects are less likely. Since the investigator is hidden in this type of observation there is less chance that their direct or indirect behaviour will have an impact on the performance of the participants. As a result, there is less chance of demand characteristics occurring whereby the participant tries to guess the aim of the investigation and act accordingly, since they are unaware that they are being observed. This means that the participants’ behaviour seen will be more natural and representative of their everyday behaviour.

There are ethical issues associated with the covert method of observation inherent within its design. As participants are not aware they are taking part in an investigation, they

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cannot give fully informed consent nor exercise their right to withdraw. That being said, it is perfectly acceptable to observe human behaviour in a public place such as a shopping centre. This means that an assessment is made by the investigator before the observation begins to ensure that no privacy laws are being violated.

Overt Observations An overt observation is an observational technique where the observations are ‘open’ and the participants know/are aware that they are being observed. For example, filming publicly (overt non‐participant) or joining a class and informing the other students that you are carrying out an observation (overt participant). Evaluating Overt Observations A strength of the overt method is that it is often more ethical than the covert method. Since the

participants are aware that their behaviour is being observed for the purposes of a psychological investigation, it is possible to inform them in advance of the aims and thus obtain informed consent. This awareness of participation also allows participants to exercise their right to withdraw themselves or their data from the investigation, before, during or after the observation is conducted. As a result, the reputation of psychological research as being ethical is protected.

A drawback of using an overt style of observation is the possibility of investigator effects. It is possible for a bias to occur whereby what the investigator does influences the behaviour of the participants in a way which was not intended (e.g. body language or facial expressions). As a result, the participants may change their behaviour through demand characteristics and act in accordance with their perception of the research aims. Therefore, authentic and natural behaviour is not being observed, thus reducing the internal validity of the observation because it is overt.

Participant Observations In a participant observation, the person who is conducting the observation also takes part in the activity being observed. It can be either covert (a group member quietly observing others without their knowledge) or overt (a group member using a camera to record the behaviour of other members with their full knowledge). Evaluating Participant Observations A strength of using participant observations in psychological research is that the researcher can obtain

in‐depth data. Since the observer is in close proximity to the participants, they are able to gain a unique insight into the phenomenon in question. In addition, through participating they are unlikely to overlook any behaviour that, as an external observer, would be missed due to nuances only seen by becoming a participant of the activity itself. This means that a comprehensive understanding of human behaviour can be achieved using this method of observation.

A disadvantage of using the participant observation method is the possibility of investigator effects and the impact of the researcher on the other participants’ behaviour. The mere presence of the investigator as a member within the group might influence the participants’ behaviour in a way which was not intended. Consequently, the participants may change their behaviour through demand characteristics and act in accordance with their perception of the research aims. Consequently, natural behaviour is not being observed, thus reducing the internal validity of the observation because the investigator is a participant.



Non‐Participant Observations In a non‐participant observation, the person who is conducting the observation does not participate in the activity being observed. This type of observation is quite common in educational settings, as in teacher evaluations, for example, when an observer sits in the corner of the room and watches the lesson. The aim is for the observer to be as unobtrusive as possible and not engage with any of the activities happening. Evaluating Non‐Participant Observations An advantage of using a non‐participant observation method is that investigator effects are less likely

compared to a participant observation. The researcher is often observing at a distance from the participant(s) and in some situations, not visible to them at all. As a result, the behaviour of the investigator is unlikely to have a negative impact on the behaviour of the participants. This means that behaviour observed is more likely to be representative of natural and unaltered human conduct.

There are disadvantages associated with the non‐participant method of observation. Due to a lack of proximity to the participant behaviour being studied, the researcher might miss behaviours of interest. This means that unique insights which contribute to the understanding of the human behaviour being observed will be overlooked because of not being involved personally.

Naturalistic Observations A naturalistic observation is an observation carried out in an unaltered setting in which the observer does not interfere in any way and merely observes the behaviour in question as it happens normally. An example of this would be an observation carried out in a shopping centre as people go about their daily business. Evaluating Naturalistic Observations A strength of using naturalistic observations is that a higher level of ecological validity can be achieved.

In an observation of this design, the researcher records naturally occurring behaviour in the original environment in which it ordinarily occurs. This means that the behaviour being recorded is likely to be more representative of everyday activities and reflect spontaneous actions that sometimes occur incidentally.

There are issues of ascertaining reliability with naturalistic observations. Since observations of this kind record behaviours which are occurring naturally as they unfold it is difficult, if not impossible, for the exact same conditions to be replicated. Consequently, the test‐retest method of checking reliability cannot be used with this type of observational design, as the researcher is not in control of variables. This means that research attempting to understand human behaviour using naturalistic observations often lacks replicability.

Controlled Observations A controlled observation is conducted under strict conditions, such as in an observation room or laboratory setting where extraneous variables (such as time of day, noise, temperature and visual distractions) can be controlled to avoid interference with the behaviour being observed. Sometimes one‐way mirrors can be used for these types of observations. If the participants know they are being observed, this is an overt method which is most commonly the case for controlled observations. Evaluating Controlled Observations A strength of controlled observations is that they can be replicated to check for reliability. By their very

nature, the variables are highly controlled in this type of observational design. This means that standardised procedures, the manipulation of the independent variable and control over extraneous



variables can be repeated by the same, or different, researchers to assess the reliability.

A criticism of controlled observation is that they have a lower level of external validity. The researcher records behaviour in an artificial environment with variables subject to strict manipulation. This high level of control comes at a cost with the setting of the observation feeling quite unnatural as a result. Therefore, the participants’ behaviour may alter in response meaning that the observation no longer represents real‐life occurrences causing the ecological validity of the findings to be questionable.

Structured Observations In structured observations, the researcher uses coded ‘schedules’ according to a previously agreed formula to document the behaviour and organise data into behavioural categories. A behavioural category is when psychologists must decide which specific behaviours should be examined. This involves breaking the target behaviour (e.g. aggression) into components that can be observed and measured (e.g. hitting or kicking). Evaluating Structured Observations A strength of structured observations is that the researcher can compare behaviour between

participants and across groups. The use of operationalised behavioural categories makes the coding of the data more systematic. When there is more than one observer, the standardised behaviour schedule results in greater inter‐observer reliability. It is important for research methodologies to be consistent so that accurate comparisons can be made.

However, there may be problems with ascertaining high internal validity in a structured observation. This is because the researcher may miss some crucial behaviours during the observation which is pertinent to the aim of the investigation. As a result, the findings portrayed may not provide the full picture about the behaviour in question, as they could lack the finer details. This is a problem because what was intended to be measured was not achieved in its entirety.

Unstructured Observations An unstructured observation involves every instance of the observed behaviour being recorded and described in as much detail as possible. This is useful if the behaviour that researchers are interested in does not occur very often and is more usual with naturalistic observation. Evaluating Unstructured Observations A strength of unstructured observation is the richness of data obtained. Since behaviour is recorded in

great detail, researchers are able to obtain a comprehensive view of human behaviour. This adds to the internal validity of the observational technique.

Additionally, this type of observation is also prone to observer bias due to the lack of objective behaviour categories. This is a problem because the observer may then only record behaviour which is of subjective value to them, and not a valid representation of what is being displayed. As a result, there may be a problem with inter‐observer reliability as there will be a lack of consistency in the observations recorded.



Comparison of Observational Techniques OVERVIEW STRENGTHS LIMITATIONS

COVERT OBSERVATION

Undisclosed: Participant is not aware

Investigator effects and demand characteristics are less likely

Less ethical: lack of informed consent

OVERT OBSERVATION Participant is aware

More ethical: informed consent obtained

Investigator effects and demand characteristics are more likely

PARTICIPANT OBSERVATION

Researcher takes part (close proximity)

In‐depth data is gathered due to close proximity

Investigator effects and demand characteristics are more likely

NON‐PARTICIPANT OBSERVATION

Researcher does not take part (not close proximity)

Investigator effects and demand characteristics are less likely

Researcher might miss behaviours of interest due to lack of proximity

NATURALISTIC OBSERVATION

Takes place in naturalistic (unaltered) setting

Higher level of ecological validity

Issues with replication and ascertaining reliability

CONTROLLED OBSERVATION

Takes place in artificial (controlled) environment

Can be replicated to check reliability

Lower levels of ecological validity

STRUCTURED OBSERVATION

Behaviour is coded using behavioural categories

Higher levels of inter‐observer reliability

Less rich data can lack internal validity as researchers miss important behaviours

UNSTRUCTURED OBSERVATION

Every instance of behaviour is recorded and described

Rich data leads to greater internal validity

Lower levels of inter‐observer reliability

Exam Hint: Although there are many strengths/limitations of observations, you will notice that for each pair of observations (i.e. covert and overt) the strength of one type (i.e. covert observations have a lower chance of investigator effects) is the limitation of the opposite type (i.e. overt observations have a higher chance of investigator effects). In observations, the observer generally has the choice of two methods: time sampling or event sampling. TIME SAMPLING EVENT SAMPLING This is where an observer records

behaviour at prescribed intervals, e.g. every 10 seconds.

This is where an observer records the number of times that the target behaviour occurs, e.g. using a tally.

STRENGTH Time sampling methods allow for a better use of time since fewer observations are made.

Every behaviour of interest to the researcher, in theory, will be counted from the beginning through to the end of the observation.

LIMITATION Not every behaviour of relevance to the investigation will be counted if it occurs in between the time frames allocated.

There is the possibility that some behaviours could be missed if there is too much happening at the same time, resulting in some not being coded.



Possible Exam Questions 1. Explain how observational research can be enhanced through the use of operationalised behavioural

categories. (2 marks) 2. Explain what is meant by ‘overt observation’. (2 marks)

3. Describe what is meant by ‘participant observation’. (2 marks) 4. Explain what is meant by ‘event sampling’ in relation to observational research in psychology. (2 marks)

5. Controlled observation techniques have been used in the Strange Situation to investigate cultural

variations in attachment. Suggest one advantage of using controlled observation in psychological research. (2 marks)

Exam Hint: It is important for students to only express one advantage of using a controlled observational method for this question using the ‘name and explain’ method of elaboration. 6. Briefly explain how a psychologist could improve her research by conducting observations in a

controlled environment. (4 marks) 7. Explain the difference between a participant observation and a non‐participant observation. You may

use an example to support your point. (4 marks) Exam Hint: Note that this question is asking for a difference and not a definition of each observational method, so the response must be tailored accordingly.

8. Identify and explain one strength and one limitation of conducting naturalistic observations. (4 marks)

9. A developmental psychologist was interested in investigating the effects of early and late adoption on

future aggressive behaviour in children. She compared the behaviour of children who had been adopted before the age of two with children who had been adopted after the age of two. The children were observed in their primary school playground when they were seven years old. Suggest two operationalised behavioural categories that the developmental psychologist could use in her observation of aggressive behaviour in children and explain how the psychologist could have carried out this observation. (4 marks)

Exam Hint: This is a context based question so explicit reference to the scenario is required to gain full credit. Note that behavioural categories such as ‘verbal aggression’ and ‘physical aggression’ would not be awarded any marks as they are not operationalised. Suggestions such as ‘kicking’ or ‘swearing’ would be creditworthy as they are specific and measurable. To answer the second component of this question, most students will refer to the use of a tally chart for recording behaviours observed on an event sampling basis.



10. Read the item below and then answer the question that follows. Dr Fox was interested in the differences between male and female communication skills. Past research has investigated gender differences in this field of psychology through focusing on fluency in spoken word communication and non‐verbal communication such as body language and facial expressions.

Design an observational study for Dr Fox to be able investigate differences between males and females in non‐verbal communication when they are giving a presentation to a large audience. (12 marks) In your answer, you must refer to:

a. the task used for the participants to complete b. the behavioural categories to be implemented and how the data will be recorded c. how reliability of the data collection might be established d. ethical issues to be considered.


SELF‐REPORT TECHNIQUES Specification: Self‐report techniques. Questionnaires; interviews, structured and unstructured. Questionnaire construction, including use of open and closed questions; design of interviews. WHAT YOU NEED TO KNOW Outline and evaluate the use of questionnaires, including: open and closed questions. Outline and evaluate interviews, including:

o Structured o Unstructured

Introduction to Questionnaires Questionnaires are a type of ‘self‐report’ technique, where participants provide information relating to their thoughts, feelings and behaviours. They can be designed in different ways, and can comprise of open questions, closed questions or a mixture of both. Open Questions Open questions allow participants to answer however they wish, and thus generate qualitative data since there is no fixed number of responses to select from. Responses to these types of questions provide rich and detailed data which can provide insight into the unique human condition. Evaluation of Open Question Questionnaires A strength of using open questions is that there is less chance of researcher bias. This is especially true

if the questionnaire is also anonymous, since the participant can answer the questions in their own words, without input from the researcher providing a set number of responses. Consequently, there is less chance of the responses being influenced by the researcher’s expectations.

However, there are limitations of using questionnaires in psychological research. Participants may answer in a socially desirable way, where they try to portray themselves in the best possible light to the researcher. This means that the open response may lack validity as it is not their natural response.

Closed Questions Closed questions restrict the participant to a predetermined set of responses and generate quantitative data. There are different types of closed questions, including: checklist, Likert response scale and ranking scale. Checklist: This is a type of question

where participants tick the answer(s) that apply to them. For example: What is the highest academic qualification you hold?




GCSEs A‐levels Bachelor’s Degree Postgraduate Degree

Likert Response Scale: This is a type of question where participants rate on a scale their views/opinions on a question. For example: Psychology is the most interesting A‐Level subject. (Circle the number that applies). 1 2 3 4 5

Strongly Agree Agree Not sure Disagree Strongly Disagree

Ranking Scale: This is where participants place a list of items in their preferred order. For example: Rank the following activities according to how much time you spend on them each day. (1 = most time, 4 = least time). Talking face‐to‐face Talking on the telephone Text messaging Other (e.g. Snapchat or Instagram)

Evaluation of Closed Question Questionnaires An advantage of using closed questions is the nature of the data collected which is quantitative. This

type of data makes it easy to analyse the results statistically or in a graphical format. This is useful because direct comparisons can be made between groups of individuals. This means the researcher can look for patterns and trends in the data that can lead to further research being conducted.

There are limitations to adopting a closed question format in questionnaire research. By sticking to a predetermined list of questions, the researcher is unable to pursue and explore responses that are of particular interest. Additionally, closed questions often produce a response bias. This can happen because the participant doesn’t take the time to read all the questions properly and, for example, selects ‘yes’ for each of their answers. This means that the data generated may lack internal validity.

Questionnaire Design The following factors should be considered when designing questionnaires: Keep the terminology simple and clear. Keep it as short as possible. Be sensitive; avoid personal questions. If you must, collect personal information at the end. Do not use leading questions. Do not use questions that make assumptions or sweeping statements. Pilot and modify the questionnaire. Comparison of Open Question and Closed Question Questionnaires STRENGTHS LIMITATIONS

OPEN QUESTION

Less chance of researcher bias, and detailed answers obtained.

Participants may answer in a socially desirable way, making answers less valid.

CLOSED QUESTION

Easy to analyse quantitative data, discover trends and replicate research.

Predetermined list of questions limits responses ability to explore interesting answers. Response bias.



Introduction to Interviews Interviews are another type of self‐report technique which predominantly take place on a face‐to‐face basis, although they can also happen over the telephone. There are three different interview designs: interviews can take the form of participants just answering a predetermined list of questions (structured interviews); they can be more like a relaxed conversation between friends (unstructured interviews); and, although it is not on the specification, it is also important to recognise that many fall between the two (semi‐structured interviews). Responses are usually recorded, with the use of an interview schedule that the interviewer completes and/or audio or video recording, with the informed consent of the interviewee(s). Structured Interviews Structured interviews have the questions decided on in advance and they are asked in exactly the same order for each interviewee taking part. The interviewer uses an interview schedule and will often record the answers to each question by taking notes/ticking boxes on their schedule. Evaluation of Structured Interviews An advantage of using structured interviews in psychological research is that the quantitative

(numerical) data is easier to statistically analyse. This is useful because direct comparisons can be made between groups of individuals meaning that the researcher can look for patterns and trends in the data. Additionally, because the questions are standardised and asked in the same sequence every time to all participants, the interview is easily replicable to test for reliability.

There are disadvantages of using the structured interview method. It is possible that over the course of

running several interviews following the same schedule with different participants, that investigator effects may play a role. This is where the interviewer may, unconsciously, bias any responses given to the questions they ask by their tone of voice, intonations, body language and so on. Likewise, investigator effects can also occur between researchers where there is more than one researcher conducting the interviews.

Unstructured Interviews Unstructured interviews are conducted more like a conversation, with the interviewer only facilitating the discussion rather than asking set questions. Very little is decided in advance (only the topic and questions needed to identify the interviewee). Therefore, this type of interview typically produces a large amount of rich qualitative data. Answers will usually be audio or video recorded, as to write them all down as quickly as they were spoken would be impossible for the interviewer, and would also spoil the relaxed atmosphere of the unstructured interview. Evaluation of Unstructured Interviews The use of unstructured interviews can increase the validity of findings by significantly reducing the

possibility of investigator effects. The open question schedule in unstructured interviews means that the investigator does not control the direction of the conversation to meet their own preconceived agenda. Participants can justify their answers in their own words with opinions rather than trying to guess the aim of the study through any clues given. This is useful because it reduces the possibility of participants displaying demand characteristics in their interview responses.

Unstructured interviews generate large quantities of rich and interesting qualitative data. This allows the interviewer to clarify the meaning and gain further information from the participant if required to



full understand complex human behaviour. However, unstructured interviews are more time consuming and costly, as this type of interview requires a trained psychologist to administer them. A further issue with this method is that statistical analysis can be challenging, as the data collected is qualitative, making it more difficult to identify patterns and trends without undergoing a content analysis first.

Semi‐Structured Interviews Semi‐structured interviews comprise of mostly prepared questions that can be supplemented with additional questions as seen fit by the interviewer at the time. As with unstructured interviews, the interviewer can deviate from the original questions and consequently this type of interview also typically produces rich qualitative data. Evaluation of Semi‐Structured Interviews The use of semi‐structured interview can increase the validity of findings. The open questions in semi‐

structured interviews may encourage the participant to be honest in their answers, thus reducing social desirability bias as participants are able to justify their answers in their own words with opinions. However, the interviewer still retains control over the semi‐structured interview schedule compared to an unstructured interview, which can result in investigator effects which can affect the behaviour of the participants negatively.

Semi‐structured interviews generate rich and interesting qualitative data. As with unstructured interviews, this allows the interviewer to clarify the meaning of the participants’ responses and gain further information if required. This provides a unique insight into explaining human behaviour. However, as a result, analysis of such data can be more difficult, time consuming and expensive to conduct compared to quantitative data which is easier to statistically analyse without undergoing further processing beforehand.

Comparison of Different Interview Designs STRENGTHS LIMITATIONS

STRUCTURED Easier to analyse quantitative data; discover trends; replicability. Increased risk of investigator effects.

UNSTRUCTURED Less chance of demand characteristics and investigator effects. Difficult to analyse qualitative data; time consuming and expensive.

SEMI‐STRUCTURED

Rich and interesting qualitative data; less chance of social desirability bias.

Higher chance of demand characteristics in comparison to unstructured interviews.

Possible Exam Questions 1. Suggest one closed question that a researcher could use in a structured interview investigating religion.

(2 marks) 2. Explain one disadvantage of using open questions in an interview rather than closed questions. (2

marks)

3. Explain what is involved in self‐report. (3 marks) Exam Hint: This question requires students to explain that self‐report often involves questionnaires and/or interviews with suitable elaboration thereafter on how this would be conducted.



4. Dr Clamp was interested in investigating attitudes towards Brexit. She is unsure about which methodology to select for her study.

Explain the difference between a structured interview and an unstructured interview. (3 marks)

5. Two psychology undergraduates are interested in devising a questionnaire to collect data on their

campus about attitudes towards student tuition fees.

Briefly discuss the benefits for the researchers of using both closed and open questions on their questionnaire about attitudes to tuition fees. (4 marks)

6. Outline two differences between an interview and a questionnaire. (4 marks)

7. Evaluate the use of questionnaires as a research method. (4 marks) Exam Hint: Answers for this type of question need to clearly explain the strength or limitation rather than merely state them. So, to state that questionnaires are ‘quick’ gains no credit because there is no explanation as to why they are quick. Better answers will compare questionnaires to other methods such as interviews. So, to say that a questionnaire is quick in comparison to an interview because a trained researcher does not need to be present becomes a creditworthy comment. 8. Evaluate the use of self‐report techniques, including both questionnaires and interviews, in

psychological research. (8 marks) Exam Hint: Whilst this is an eight‐mark question, it is worth unpicking the demands to consider the different elements required for a successful answer to be produced. For example, this question could be interpreted as: 1) Evaluate questionnaires (4 marks); and 2) Evaluate interviews (4 marks).



CORRELATIONS Specification: Correlations. Analysis of the relationship between co‐variables. The difference between correlations and experiments. Analysis and interpretation of correlation, including correlation coefficients. WHAT YOU NEED TO KNOW Outline and evaluate correlational techniques. Outline the difference between correlations and experiments. Interpret correlation coefficients. Introduction to Correlational Techniques Correlational techniques are non‐experimental methods used to measure how strong the relationship is between two (or more) variables. In an experiment, the effect of an independent variable upon the dependent variable is measured; however, in correlational studies the movement and direction of co‐variables in response to each other is measured. There is no claim of a cause and effect relationship, although after a correlational study has been conducted, further research will often be conducted to determine if one variable is in fact affecting the other. A real‐world example of this is seen with cigarette‐smoking and lung cancer: first it was noticed that there was a positive correlation between the number of cigarettes smoked and the likelihood of developing lung cancer. Later, this research was extended and a cause and effect relationship was discovered between cigarette‐smoking and lung cancer. There are different types of correlation: Positive correlation: As one variable increases the other variable increases. For example – height and

shoe size. Negative correlation: As one variable increases the other variable decreases. For example – the GCSE

grades of students and the amount of time they are absent from school. Zero correlation: occurs when a correlational study finds no relationship between variables. For

example – the amount of rainfall in Wales and the number of people who have read the Lord of the Rings trilogy.

Correlation Coefficient A correlation coefficient is used to measure the strength and nature (positive or negative) of the relationship between two co‐variables. The correlation coefficient number represents the strength of the relationship and can range between ‐1.0 and +1.0. The nearer the number is to +1 or ‐1 the stronger the correlation. A perfect positive correlation has a correlation coefficient of +1 and for a perfect negative correlation it is ‐1.



Scattergram A scattergram (sometimes called a scattergraph) is a graph that shows the correlation between two sets of data (co‐variables) by plotting points to represent each pair of scores. It indicates the degree and direction of the correlation between the co‐variables, one of which is indicated on the X‐axis and the other on the Y‐axis.

Evaluation of Correlational Techniques Correlational studies are an ideal place to begin preliminary research investigations. Since they

measure the strength of a relationship between two (or more) variables, this can provide valuable insight for future research. This type of analysis can be used when a laboratory experiment would be unethical as the variables are not manipulated, merely correlated. In addition, secondary data can also be used in correlational studies which alleviates the concern over informed consent as the information is already in the public domain, e.g. government reports.

There are limitations associated with using the correlational method. It is not possible to establish a cause and effect relationship through correlating co‐variables. This means a researcher cannot conclude that one variable caused the other variable to increase/decrease as there could be other factors which influenced the relationship – referred to as the third variable problem. Moreover, correlations only identify linear relationships and not curvilinear. For example, the relationship between temperature and aggression is curvilinear, that is the relationship is positive to a point; however, at very high temperatures aggression declines.



Summary of Correlational Techniques STRENGTHS LIMITATIONS

CORR

ELAT

IONA

L TE

CHNIQU

ES

Can be used when a laboratory experiment would be unethical as the variables are not manipulated, only correlated.

Not possible to establish cause and effect relationships through conducting a correlation.

Measure the strength of a relationship between variables, allowing for further research to be conducted.

Can only identify linear relationships and not curvilinear.

Possible Exam Questions 1. A psychological study recorded the number of hours that children spent in a day care setting from birth

to three years old, and asked each child’s primary care giver to rate their child for aggression. The study found that, as the number of hours spent in day care went up, the parents rating of aggression also went up. What type of correlation is this research indicating? (1 mark)

Exam Hint: Most students will be able to identify correctly that this is in fact a positive correlation because as one variable increases, so does the other. 2. Discuss why it might be more appropriate for a researcher to use a correlation study rather than an

experiment. (3 marks)

Exam Hint: Answers which simply state that a correlational study looks for a relationship and experiments investigate differences will only gain one mark here. In order to access further marks, students must be able to explain issues around manipulation of variables and ethics. 3. Outline one strength and one weakness of using correlational methods in psychological research. (4

marks) Exam Hint: Many students can consider the main weakness of correlations but struggle to correctly outline a strength. Strengths include the ability to study the relationship between variables that occur naturally, or to measure things that cannot be manipulated experimentally.



CASE STUDIES [A‐LEVEL ONLY] Specification: Case studies. WHAT YOU NEED TO KNOW Outline and evaluate the use of case studies in psychology. Case Studies The purpose of a case study is to provide a detailed analysis of an individual, establishment or real‐life event. A case study does not refer to the way in which the research was conducted, as case studies can use experimental or non‐experimental methods to collect data. For example, a researcher may want to interview the participants, provide a questionnaire to their family or friends and even conduct a memory test under controlled conditions to provide a rich and detailed overview of human behaviour. Case studies are often used where there is a rare behaviour being investigated which does not arise often enough to warrant a larger study being conducted. A case study allows data to be collected and analysed on something that psychologists have very little understanding of, and can therefore be the starting point for further, more in‐depth research. Examples of famous case studies in psychology include: HM, Phineas Gage, Little Albert and Little Hans. Likewise, psychologists have studied important world events such as the 9/11 terrorist attack in America and the riots which began in London and spread throughout the UK in 2011. Evaluation of Case Studies There are methodological issues associated with the use of case studies. By only studying one

individual, an isolated event or a small group of people it is very difficult to generalise any findings to the wider population since results are likely to be so unique. This therefore creates issues with external validity as psychologists are unable to conclude with confidence that anyone beyond the ‘case’ will behave in the same way under similar circumstances, thus lowering population validity.

An issue in case studies, particularly where qualitative methods are used, is that the researcher’s own

subjectivity may pose a problem. In the case study of Little Hans, for example, Freud developed an entire theory based around what he observed. There was no scientific or experimental evidence to support his suggestions from his case study. This means that a major problem with his research is that we cannot be sure that he objectively reported his findings. Consequently, a major limitation with case studies is that research bias and subjectivity can interfere with the validity of the findings/conclusions.

A strength of the case study approach is

that it offers the opportunity to unveil rich, detailed information about a situation. These unique insights can often be overlooked in situations where there is only the manipulation of one variable in order to measure its effect on another. Further to this, case studies can be used in circumstances which would not be ethical to examine experimentally. For example, the case study of Genie (Rymer, 1993) allowed researchers to understand the long‐term effects of failure to form an



attachment which they could not do with a human participant unless it naturally occurred.

Possible Exam Questions 1. Researchers often use a range of techniques to gather information in case studies of individuals,

institutions or events. Suggest one technique which the psychologist could use in a case study. (1 mark) Exam Hint: Referring to the use of meta‐analysis here would not be appropriate: be specific and name an experimental or non‐experimental research method (e.g. interview). 2. Define the key term ‘case study’. (2 marks) Exam Hint: Better answers will refer to the fact that a case study is an in‐depth investigation of a single person, usually over a period of time, using a range of methods to collect data. Students can also illustrate their answers with relevant examples, such as Freud’s Case Study of Little Hans. 3. Explain one limitation of using a case study as a method of investigation. (2 marks) Exam Hint: Most students will explain a lack of population validity here: since a case study is of a unique person this means that it is difficult to generalise the results to the wider population as they may not behave in the same way.

4. Explain one strength of using a case study methodology in psychology. (3 marks)

5. Scarlett has an incredible memory. She can see a pack of playing cards only once and then recall the

order correctly. A psychologist was interested in investigating this phenomenon further by focusing on Scarlett and her amazing memory in different situations and contexts.

The scenario illustrated above is an example of a case study methodology. Explain one strength and one weakness of this research method. (4 marks)

Exam Hint: For this question, there is one mark each for identifying one appropriate strength and one appropriate weakness, and the third and fourth mark come from suitable elaboration of these points. For example: a strength of using a case study to study memory is that the data gathered will be rich in detail which will give a unique insight into the individual case of Scarlett and her memory.

6. Evaluate the use of case studies in psychological research. Refer to evidence in your answer. (6 marks)



AIMS, HYPOTHESES, IVS & DVS Specification: Aims: stating aims, the difference between aims and hypotheses. Hypotheses: directional and non‐directional. Variables: manipulation and control of variables, including independent and dependent. WHAT YOU NEED TO KNOW Outline the aim for a psychological investigation and differentiate between an aim and a hypothesis. Identify the independent and dependent variables in a psychological investigation. Outline operationalised hypotheses for psychological investigations, including:

o Directional o Non‐directional hypotheses

Writing Aims for Investigations Before a researcher considers the aim of the experiment, there is always a research question they are trying to answer. For example: ‘Does hunger affect memory for food‐related words?’ Thereafter, the researcher creates their aim: To examine the effect of hunger on memory of food‐related words. Exam Hint: Always start the wording of an aim with ‘To examine the effect of…’ Identifying Independent and Dependent Variables The independent and dependent variables are the vital components of any experiment. Their presence is how you identify whether a study is following an experimental methodology or not. If there is no independent variable or dependent variable then the study is non‐experimental. Independent Variable (IV) – The variable that the researcher manipulates and which is assumed to

have a direct effect on the dependent variable (DV).

Dependent Variable (DV) – The variable that the research measures. The variable that is affected by changes in the independent variable (IV).

Exam Hint: It is unlikely that you will be asked to define what is meant by the terms IV and DV. You are more likely to be asked to identify the IV and DV within a scenario. For example: A psychologist showed participants 50 different cards, one at a time. Each card had two unrelated words printed on it, e.g. balloon or rabbit. Participants in one group were instructed to form a mental image to link the words. Participants in the other group were instructed to simply memorise the words. After all the word pairs had been presented, each participant was shown a card with the first word of each pair printed on it and asked to recall the second word. What is the independent variable (IV) in this study? (2 marks) Answer: Whether participants were instructed to form a mental image to link the unrelated word pairs or simply instructed to memorise the word pairs without a memory strategy. What is the dependent variable (DV) in this study? (2 marks) Answer: The number of word pairs correctly recalled by the participants in each condition. Exam Hint: Before answering any question where you are required identify the IV and DV, read the extract carefully and underline the IV and DV. Once you have identified what you think the IV is, ask yourself the following question: “Is it possible for the experimenter to manipulate this variable?”. If your answer is ‘yes’ then this is likely to be your IV. If your answer is ‘no’ then this is unlikely to be the correct IV.



Writing Operationalised Hypotheses for Experiments A hypothesis is a clear and precise prediction about the difference or relationship between the variables in the study. Operationalisation is the term used to describe how a variable is clearly defined by the researcher. The term operationalisation can be applied to independent variables (IV), dependent variables (DV) or co‐variables (in a correlational design). The hypothesis should always contain an operationalised independent variable and dependent variable. For example, if the aim of a study was: to examine the effect of hunger on the memory of food‐related words, the IV is hunger levels (hungry vs. not hungry) and the DV might be the number of food‐related words correctly recalled. There are two types of experimental hypotheses: Directional hypothesis: predicts the specific nature (direction) of the difference between two or more

variables. This prediction is typically based on past research, accepted theory or literature on the topic. A directional hypothesis is sometimes called one‐tailed. Examples of key words used in a directional hypothesis are: higher, lower, more, less, increase, decrease, positive and negative.

Example: There will be a significant increase in the number of food‐related words correctly recalled by the participants who are hungry, in comparison with those who are not hungry. Non‐directional hypotheses: predicts that a difference will exist between two or more variables

without predicting the exact direction of the difference. This is usually because previous research has been inconclusive, and the specific nature (direction) of the effect of the IV on the DV cannot be predicted confidently. Non‐directional hypothesis are sometimes called two‐tailed. The key word used in a non‐directional hypothesis is difference.

Example: There will be a significant difference in the number of food‐related words correctly recalled for participants who are hungry, in comparison with those who are not hungry.

Note: In the above non‐directional hypothesis, the IV (hunger levels) is shown to have an effect on the DV (number of food‐related words correctly recalled) BUT we have not said if the effect will be more/less. Possible Exam Questions 1. Identify the directional hypothesis from the list below. (1 mark)

a) There will be a difference in the driving ability of male and female drivers. b) There will be a relationship between number of hours sleep and concentration levels. c) There will be no difference between the amount of pasta eaten each month and ability to speak a

foreign language and any difference seen will be due to chance. d) There will be a significant increase in the happiness rating of students who can leave lessons five

minutes early each day compared to those who are kept behind. 2. A researcher is interested in studying the influence of caffeine on attention span through conducting a

laboratory experiment. Identify the most likely independent variable (IV) for this investigation. (1 mark) a) Gender of the participant b) Ability to stay focused on a task c) Drinking a cup of coffee or a glass of water d) Location of the memory test

3. Suggest one reason why a psychologist might choose a non‐directional hypothesis over a directional

hypothesis. (2 marks)

4. Explain the difference between a directional and a non‐directional hypothesis. (2 marks)



5. A psychologist is interested in studying the effects of staying up late and not getting the recommended eight hours sleep per night, compared to having an early night to get lots of rest on student performance in a maths test at school the next day. a) Identify the dependent variable (DV) in this investigation. (1 mark) b) What is the difference between an aim and a hypothesis? (2 marks) c) Explain what is meant by the term ‘operationalisation’. (2 marks) d) How does a researcher decide whether to select a directional or a non‐directional hypothesis? (2

marks) 6. A cognitive psychologist was interested in investigating whether memory for words presented with a

visual representation alongside it, such as a picture, was better than memory for words presented alone. The researcher used an independent groups design with participants recruited through opportunity sampling at a university campus open day. Group A: participants will be given two minutes to learn a list of 15 words before being asked to recall them freely in any order. Group B: participants will be given two minutes to learn the same list of 15 words, but this time each word will presented with a visual representation alongside it. For example, the word ‘banana’ will have a picture of a banana next to it. Participants will then be asked to recall the 15 words freely in any order.

Suggest an appropriate non‐directional hypothesis for this experiment. (2 marks)

Exam Hint: Students are required to operationalise the IV and DV to score full marks, for example: ‘There will be a difference in the number of words correctly recalled when words are presented with pictures in comparison to without pictures’. ‘There will be a difference in words recalled in condition one and condition two’ is not operationalised and would therefore only receive one mark. Students must also make sure that their hypothesis does not refer to a correlation by using the term ‘relationship’ or ‘link’ when this is clearly an experiment of difference. 7. Research suggests that the cognitive interview technique can increase the accuracy of eyewitness

testimony compared to the standard police interview. Lakin et al. wants to test the accuracy of eyewitness testimony following a real‐life bank robbery where staff and customers were held at gun point, to increase the chances of prosecuting the correct perpetrators. Twelve of the individuals present on the day of the crime agreed to take part in the study. The researchers decide to use an independent measures design.

Suggest a suitable hypothesis for this investigation. (3 marks)

Exam Hint: To achieve full marks here the answer must show understanding of what was being manipulated by the researcher (IV – cognitive interview or standard police interview) and what was being measured in this study (DV) which was an increase in accuracy of eyewitness testimony.



SAMPLING Specification: Sampling: the difference between population and sample; sampling techniques including: random, systematic, stratified, opportunity and volunteer; implications of sampling techniques, including bias and generalisation. WHAT YOU NEED TO KNOW Identify the difference between a population and a sample. Outline and evaluate the following sampling techniques:

o Random o Systematic o Stratified o Opportunity o Volunteer

Evaluate the sampling techniques in relation to bias and generalisation. Introduction to Sampling Techniques Sampling involves selecting participants from a target population. The target population is the particular subgroup to be studied, and to which the research findings will be generalised. A target population is usually too large to study in its entirety, so sampling techniques are used to choose a representative sample. For example, a sample could be 20 A‐level students from a school that has 500 A‐level students in total. Sampling Techniques Psychologists use sampling techniques to choose people to represent the target population. If the sample is representative then psychologists can generalise the results to the target population with more credibility. There are five common types of sampling: Random Systematic Stratified Opportunity Volunteer

Random Sampling With random sampling, every member of the target population has an equal chance of being selected. This involves identifying everyone in the target population and then selecting the number of participants you need in a way which gives everyone an equal chance of being selected, such as pulling names from a hat, or using a computer software package which generates names/number randomly and without bias. If a researcher was trying to achieve a random sample from 500 A‐level students in a school, they would place the name of each student on role into a hat/computer name generator and



then select the first 20, for example, to be participants in their study. Evaluation of Random Sampling A strength of obtaining a random sample is that it is free from researcher bias. Since the sample is

generated by a computer generator or by selecting names from a hat the researcher does not have any input into who is selected. This significantly reduces the possibility of them choosing a biased sample of participants who would serve to support their aims. This means that the sample is likely to be representative so can be generalised to the target population.

There are drawbacks associated with the random sampling procedure. Ensuring that everyone in the

target population has an equal chance of being selected is a difficult and time consuming task. It is also a possibility that individuals who are picked may be unwilling to take part. This results in the sample being more akin to a volunteer sample.

Systematic Sampling With systematic sampling, a predetermined system is used to select participants.

For example, every fifth person is chosen and the same interval is then consistently applied to the whole of the target population such as the 10th, 15th, 20th person and so on. If a systematic sample of 500 A‐level students in a school was required, a researcher would list every student on role against a number, perhaps listed in alphabetical order, and then chose every 10th person to achieve a sample of 20 participants for their study (e.g. person 10, 20, 30, etc.) Evaluation of Systematic Sampling An advantage of using a systematic sampling system is that it is free from researcher bias. Since the

researcher is not selecting participants by choice, but by following a predetermined system, this reduces any potential influence that the investigator may have over obtaining the sample.

However, the systematic sampling method may not be truly unbiased. It might be that every Nth person has a particular characteristic in common, for example being right‐handed. Although it would be fairly unlikely and unlucky to get a sample who were all similar on a particular trait, it remains a possibility with using this technique. Therefore, the sample generated may not be representative meaning generalisation to the target population would be more difficult.

Stratified Sampling In stratified sampling, subgroups within a population are identified. Participants are obtained from each stratum (‘layer’ or category) in proportion to their occurrence within the population. For example, if a class of A‐level psychology had 20 students: 18 males and 2 females, and a researcher wanted a sample of 10 to participate in their study, the sample would consist of 9 males and 1 female, to



represent this population proportionally. Evaluation of Stratified Sampling A strength of obtaining a stratified sample is that it is largely free from researcher bias. In this

technique, the sample is generated randomly once the subcategories/strata have been identified. This significantly reduces the possibility of the researcher choosing a biased sample of participants who would serve to support their aims. This means that sample is likely to be representative because each particular subgroup, if selected appropriately, will be represented within the sample. This means that any findings generated from research with a stratified sample can be gener

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AQA A Level Psychology Topic Companion · AQA A LEVEL Psychology topic companion: RESEARCH METHODS Page 5 A strength of using natural experiments is the unique insights gained into