research methods

Question 1

independent variable

Answer 1

is the one that the experimenter manipulates/changes or naturally changes. The different variations of the IV are called the conditions of the experiment.

Question 2

dependent variable

Answer 2

is the variable that the experimenter measures to see whether the IV had had any effect on it.

Question 3

what is operationalising variables

Answer 3

means making a variable clear, precise and unambiguous. It is the process of devising a way of manipulating or measuring something so that another person knows what has been done.

Question 4

aggression from children

operationalise this

Answer 4

the frequency of aggressive acts e.g hit, shout, pushes, obsereved in a playground

Question 5

memory

operationalise this

Answer 5

score on a memory test out of 25

Question 6

what are extraneous varibles

Answer 6

are any variable other than the IV which could affect the DV. These are things which a researcher aims to identify before an experiment and put measures (controls) in place to reduce or eliminate. Possible extraneous variables/controls will depend on the nature of the research study. It is easier to control for extraneous variables in some types of studies than others. For example, research that takes place in controlled artificial conditions, will have greater control of extraneous variables, than research in natural settings.

Question 7

types of extraneous variables

Answer 7

1. situational
2. participanant

Question 8

situational variables

extraneous

Answer 8

variables connected with the research situation. For example, the time of day, location, materials given to participants etc.

Question 9

participant variables

extraneous

Answer 9

variables connected with the research participants. For example, age, gender, intelligence, profession etc.

Question 10

possible controls for situational variables

Answer 10

• Standardisation: keep everything the same for each participant. All participants should be subject to exact same instructions, experience, environment, information etc.
• Counter-balancing: Order effects can occur in a repeated measures design. In counter-balancing half the participants complete the conditions in the opposite order to the other. E.g., Condition A followed by B, Condition B followed by A (see exp design).

Question 11

possible controls for participant variables

Answer 11

• Considering experimental design: Best for controlling participant variables –are matched pairs and repeated measures designs.

* Random allocation: in an independent measures design, participants should be randomly allocated to the conditions of the study to try to ensure participant variables such as intelligence don’t become confounding variables. Participant variables should then be evenly spread across the two conditions. This can also help reduce investigator effects, so the researcher does not select which participants are in which conditions.

Question 12

what are demand characteristics

Answer 12

This is when participants change their behaviour as a result of the perceived demands of the study

Question 13

examples of demand characteristics

Answer 13

• Participants may worry about being in a psychological study and **want to appear ‘normal’, this may change their behaviour and they may behave in ways they wouldn’t do normally. **
  Participants may try to guess what the investigation is about then behave in the way they think the investigator wants them to.
• Or they may deliberately try to behave in an unexpected way, this is called the screw-you effect.
• Participants might just try to ‘look good’ (social desirability) and behave out of character or not tell the truth. This can be a problem for questionnaires on sensitive issues

Question 14

examples of controls/ways to minimise demand characteristics

Answer 14

• **Single-blind procedure: **This is when participants do not know what condition of a study they are in.
• **Deception: **If participants are not told the true aim/purpose of the study, there is less chance of participants changing their behaviour.

Question 15

what are investigor effects

Answer 15

This is when researchers can (consciously or unconsciously) influence the results of a study.

Question 16

examples of investigator effects

Answer 16

• Physical characteristics of investigators may influence results, such as age or ethnicity. For example, male participants may not want to admit to sexist attitudes to a female researcher.
• Less obvious personal characteristics of investigators like accent or tone of voice. For example, participants may react differently to someone with a stern voice and demeanour.
• Researcher bias - Investigators may be unconsciously biased in their interpretation of data and find what they expect to find. They could also behave in different ways to participants based on their expectations/knowledge.

Question 17

examples of controls/ways to minimise investigator effects

Answer 17

• Randomisation: Use of chance to reduce the researcher’s influence on investigation e.g., order of word list or tasks could be randomly generated, or participants randomly allocated to their conditions in the study.
• **Double blind: ** This is when neither participants or the researcher knows which conditions the participants are in.

* Inter-rater reliability: Using more than one-researcher and comparing their results e.g., their ratings or observations.

Question 18

what is a hypothesis

Answer 18

a testable statement regarding the expected results of a study. There are different types of hypotheses.

Question 19

what is a null hypothesis

Answer 19

which states no difference/relationship and that any effect will be due to chance.

Question 20

what is an alternative hypothesis

Answer 20

is a precise testable statement about what is expected to happen. For an experiment it will predict the difference in the IV/DV f
or a correlational study it will predict the type of relationship.

Question 21

what is a Non-directional (two-tailed) hypothesis

Answer 21

– predicts there will be an effect, but doesn’t predict the direction of the results. Again, these are worded differently for an experiment and for a correlation

Question 22

what is a Directional (one-tailed) hypothesis

Answer 22

– predicts the expected direction of the results (so which group will do better in an experiment, or whether a relationship will be positive or negative.

Question 23

what is a lab experi

Answer 23

Take place under controlled conditions in an artificial environment
The IV is manipulated (changed). The effect on the DV is measured.

Question 24

what is a field experi

Answer 24

Take place in the participants’ natural environment.
The IV is manipulated. The effect on the DV is measured.

Question 25

what is a natural experi

Answer 25

The IV is not manipulated, it changes naturally (e.g. studying a culture’s aggression before and after the introduction of TV).
The effect on the DV is measured.

Question 26

what is a quasi experi

Answer 26

These can take place in a laboratory or natural setting.
The IV varies due to being a characteristic of the participants (age, gender etc). It cannot be manipulated.

Question 27

strengths of lab experi

Answer 27

The high level of control allows replication; other researchers can repeat the experiment to check the reliability of the results.

As all other variables are controlled, any change in the DV must be caused by the manipulation of the IV, so a cause and effect relationship can be determined.

Question 28

strengths of field experi

Answer 28

Ecological validity is high as participants are in their natural environment and the situation is likely to reflect those in real life.

Participants may not know they are participating in a study; therefore they are less likely to display demand characteristics.

Question 29

strengths of natural experi

Answer 29

Natural experiments allow research where the IV can’t be manipulated for ethical or practical purposes.

Allows researchers to study real life issues so ecological validity is very high.

Question 30

strength of quasi experi

Answer 30

Can be carried out under controlled conditions therefore can be replicable and extraneous variables can be controlled.

Question 31

weaknesses of lab experi

Answer 31

Lack ecological validity. The setting is artificial and unlike real life. So participants don’t behave naturally and it can be difficult to generalise the results to other situations.

Participants are aware they’re being experimented on so may alter their behaviour and display demand characteristics.

Question 32

weaknesses of field experi

Answer 32

Reliability is low because the researcher can’t control the environment completely. So it is difficult to replicate the study to check the consistency of the results.

Lack of control means that extraneous and confounding variables could affect the dependent variable, reducing the internal validity of the study.

Question 33

weaknesses of natural experi

Answer 33

Random allocation of participants into conditions is not possible, so there may be uncontrolled confounding variables reducing the internal validity of the study.

Natural experiments are very difficult, if not impossible, to replicate as exactly the same conditions are unlikely to occur again.

Question 34

weakness of quasi experi

Answer 34

Random allocation of participants into conditions is not possible, so there may be uncontrolled confounding variables reducing the internal validity of the study

Question 35

what are the experimental methods

Answer 35

1. lab
2. natural
3. field
4. quasi

Question 36

what are the experimental designs

Answer 36

1. independent groups
2. repeated measures
3. matched pairs

Question 37

what are independent groups

Answer 37

Testing different groups of people for each condition of the experiment. Participants are randomly allocated and take part in one condition only

Question 38

strengths of independent groups

Answer 38

Order effects are not a problem as participants only do one condition of the study so will not be affected by practice or fatigue.
Less likely to display demand characteristics as only taking part one condition.

Question 39

weaknesses of independent groups

Answer 39

Participant variables/individual differences could affect the results as there are different groups doing each condition, e.g. one group may have naturally better memories than the other.

Question 40

how to deal with weaknesses of independent groups

Answer 40

Randomly allocating participants to conditions should mean characteristics are evenly spread between the conditions.

Use a matched pairs design to make the groups as similar as possible to reduce participant variables.

Question 41

what is repeated measures

Answer 41

Testing the same group of people for each condition - the same people are used repeatedly. Participants take part in more than one condition.

Question 42

strength of repeated measiures

Answer 42

Participant variables are not an issue as the same group of participants is used for each condition.

Question 43

weaknesses of repeated measiures

Answer 43

Demand characteristics are more likely

Order effects could influence the results as the same group of participants is used for each condition. So performance could get better in the second condition due to practice, or decline due to fatigue.

Question 44

how to deal with weaknesses of repeated measiures

Answer 44

Counterbalancing – half the group does condition 1 first, the other half does condition 2 first. Then repeat. This minimises order effects such as practice and fatigue.

Question 45

what is matched pairs

Answer 45

Participants take part in one condition of the IV but are matched on a relevant variable to someone in the other condition and their data is ‘paired’

Question 46

strengtsh of matched pairs

Answer 46

Participants take part in one condition of the IV but are matched on a relevant variable to someone in the other condition and their data is ‘paired’

Question 47

weakness of matched pairs

Answer 47

It is time consuming and it is difficult to have groups matched on every characteristic that could affect the results.

Question 48

what are correlational studies

Answer 48

Correlational studies are different from experiments in that they look at the relationship between two variables rather than looking for a difference between conditions of an IV. Correlations **measure the strength and direction of relationships between co-variables **and are plotted onto a scattergram.

Question 49

types of correlations

listed

Answer 49

1. positive
2. negative
3. no correlation

Question 50

what is a positive coreelation

Answer 50

is where one co-variable increases as another co-variable increases, for example, number of ice creams sold increases as the temperature increases.

Question 51

what is a negative coreelation

Answer 51

is where one co-variable decreases as another co-variable increases, for example, heating bill decreases as temperature increases.

Question 52

what is no correlation

Answer 52

no evident relationship between variables

Question 53

correlation coefficent

Answer 53

The type/direction of a correlation (e.g., positive or negative) will be indicated by the + or – sign.

The strength of a correlation is indicated by the value. The closer to ‘0’ the weaker the correlation, the closer to ‘1’ the stronger the correlation

Question 54

correlation hypothesis

Answer 54

Hypotheses written for correlations are not the same as those for experiments. There is no IV and DV in a correlation

The hypothesis has to clearly state the relationship between the two variables and the variables must be operationalised. They can still be directional or non-directional, or null.

Directional: There will be a positive correlation/relationship between the price of a chocolate bar and the tastiness rating /20 (Directional can be positive or negative correlation)
Non-directional: There will be a correlation between the price of a chocolate bar and the tastiness rating/20
Null: There will be no correlation between the price of a chocolate bar and the tastiness rating/20

Question 55

evaluation of correlations

strengths

Answer 55

😊No manipulation required: Can be used to research topics that are sensitive/ otherwise would be unethical, as no deliberate manipulation of variables is required.
😊 Useful technique: Correlations can be very useful as a preliminary technique, allowing researchers to identify a link that can be further investigated through more controlled research.

Question 56

evaluation of correlations

weakness

Answer 56

No cause and effect: Correlations only identify a relationship they **do not identify which variable causes which **so cannot establish cause and effect. It is not clear which variable has caused the change in the other. There might also be a third variable present which is influencing one of the co-variables, which is not considered.

Correlations can only measure linear relationships. For example, correlations can’t show the relationship between temperature and aggression as it is curved. As temperature increases, aggression levels increase up to a point. Then any further increases in temperature leads to a decline in aggression

Question 57

what are obseration techneiques

Answer 57

involve watching and recording behaviour. They are can be used as part of an experiment as a means of measuring the dependent variable so are often a technique which is used alongside other methods.

Question 58

types of observation

listed [6]

Answer 58

1. controlled
2. naturalsitic
3. overt
4. covert
5. participnat
6. non-participant

Question 59

what is a controlled observation

Answer 59

These take place in an artificial laboratory setting. The researcher manipulates some aspect of the environment.

Question 60

strengths of controlled observation

Answer 60

High level of control. The behaviour being observed can be isolated and the environment can be manipulated to make measurement of this behaviour easier and more objective.

Question 61

weaknesses of controlled observation

Answer 61

The environment is artificial so behaviour observed may be unnatural and not reflect how people behave in real life (ecological validity is low).

Question 62

what is a naturalistic observation

Answer 62

These take place in a real life, natural environment where no manipulation is made and everything has been left as it is normally.

Question 63

strengths of naturalistic observation

Answer 63

Behaviour observed is likely to be natural so findings can be generalised to everyday life (ecological validity is high).

Question 64

weaknesses of naturalistic observation

Answer 64

The environment can’t be controlled so extraneous variables could be affecting the participants’ behaviour.
Difficult to replicate as exactly the same situation is unlikely to reoccur.

Question 65

what is an overt obseravtion

Answer 65

The participants know their behaviour is being watched and recorded and for what purpose.

Question 66

strengths of overt obseravtion

Answer 66

Ethically sound as participants know they are being observed and will have given informed consent. They are able to withdraw from the study at any point.

Question 67

weaknesses of overt obseravtion

Answer 67

Participants may not behave naturally if they are aware of being observed. They may show demand characteristics and change their behaviour.

Question 68

what is a covert observation

Answer 68

The participants are not aware they are being observed. The observer may have a hidden viewpoint or be behind a two-way mirror. The observer may disguise themselves as a member of the group being observed and record via a secret camera.

Question 69

strengths of a covert observation

Answer 69

Validity is high because completely natural behaviour will be observed – they show less participant reactivity.

Question 70

weaknesses of a covert observation

Answer 70

Lack of informed consent means this type of observation raises ethical issues. However, it is ethically acceptable to observe people without their knowledge as long as they are in a public place.

Question 71

what is a participant observation

Answer 71

The researchers become part of the group or situation being observed.

Question 72

strengths of a participant observation

Answer 72

Provides greater insights into behaviour that may not be gained by an ‘outsider’.

Question 73

weaknesses of a participant observation

Answer 73

Objectivity of observation is affected by becoming part of the group being observed. The observer is likely to form their own opinions about the participants which could affect their interpretation of their behaviour.

Question 74

what is a non-participant observation

Answer 74

The researchers do not become actively involved in the behaviour being studied and observe from a distance.

Question 75

strengths of a non-participant observation

Answer 75

Lack of direct involvement ensures greater objectivity when interpreting behaviour.

Question 76

weaknesses of a non-participant observation

Answer 76

Data lacks the richness provided by participant observation, such as feelings and motivations of participants.

Question 77

what is an observational design

Answer 77

When a researcher conducts an observation, they need to design the observation carefully to ensure they are planned and they measure what they set out too. Some decisions will depend upon the type of observation and the nature of the behaviour being observed for example.

Question 78

types of observational design

Answer 78

1. structures
2. unstructed

Question 79

what is an unstructured observation

Answer 79

The researcher may simply want to write down everything they see.

Question 80

eval of unstructured observation

Answer 80

Tend to produce qualitative data which collects rich, in-depth and detailed data on behaviour.

Greater risk of observer bias as this is no objective behavioural categories – so interpretation and recording of behaviour may be influenced by the observer – It is more subjective.

Question 81

what is a structured observation

Answer 81

The researcher quantify their observations using a pre-determined list of behaviours known as a behavioural categories.

Question 82

whta are behavioural categories

Answer 82

involve breaking down the target behaviour into components that can be observed and measures. This involves deciding which specific behaviours should be examined and creating a ‘checklist’ before an observation.

Question 83

eval of structures observation

Answer 83

Using a structured observation with behavioural categories produces quantitative data which is easier to analyse and compare

The use of behavioural categories is more objective. There is less room for interpretation of different behaviours and therefore less likely to be biased due to pre-determined categories.

Lacks depth and detail, may miss important details.

Question 84

two sampling methods for recording behaviour

Answer 84

1. event
2. time

Question 85

what is event sampling

Answer 85

This involves counting the number of times a behaviour occurs in target individual or individuals. It is a ‘frequency count’ for each behaviour. The chronological order is not recorded.

Question 86

eval of event sampling

Answer 86

Event sampling is useful when the target behaviour happens infrequently and could be missed if not used and in theory every behaviour should be recorded

If the specified event is too complex, may overlook/miss important details e.g., if there are too many behaviours happening at the same time, some may not be coded.

Question 87

what is time sampling

Answer 87

The observer decides in advance that an observer records behaviour at prescribed intervals (e.g. 10 minutes every hour, or at 30 second intervals) and records the occurrence of the specified behaviour during that period only.

Question 88

eval. of time sampling

Answer 88

Can reduce the number of observations needed if only using specified time frames in a set period.

If sampling specific times only – may not be representative as a whole and may miss behaviours.

Question 89

how does inter-observer reliability work

Answer 89

• Observers should familiarise themselves and be trained with the behavioural categories, this could be part of a pilot study.
• The observers would then observe the same behaviour at the same time, but independently of each other.
• Their observations should be compared
• This should be analysed using a correlation and if 0.8 or above it Is considered reliable.

Question 90

what is a questionaire

Answer 90

A questionnaire is a set of pre-determined questions for participants to respond to. They could be completed in the presence of the researcher or could be sent through the post or emailed for participants to complete on their own and send back.
Although questionnaires are often completed anonymously – it is always important that confidentiality of response is maintained.

Question 91

constructing a questionaire

Answer 91

• When constructing a questionnaire it’s important to make sure it is something that people will actually complete and which will provide useful data.
• It is important to have clarity of questions – clearly understood and unambiguous. Questions within a questionnaire should avoid all of the following: jargon, double-barrelled questions (two questions in one), and emotive language which indicates an author’s perspective.
• A pilot study could be used to check this.
• What types of question to use (open vs closed)

Question 92

types of questions on a questionaire

give definitions

Answer 92

• Open questions invite participants to provide their own answers, they do not have a fixed range of responses.
• Closed questions have a predetermined range of answers, e.g. multiple choice, ‘yes no’ questions, and rating and Likert scales. Here are some examples.

Question 93

strengths of questionaires

Answer 93

A strength of questionnaires is that, if the researcher is not present, particularly if the questionnaire is anonymous, there is** less chance of researcher bias**, because unlike in interviews and other methods, the reduced involvement of the researcher means there is less influence on the answers and behaviours of participants, enhancing validity.

A second strength of questionnaires generally is that they are** cost-effective and time-efficient way** of gathering data as they can be administered quickly to large numbers of participants at the same time. This could enhance the generalisability of the data if there is a large data set.

Question 94

weaknesses of questionaires

Answer 94

However, although they can be administered quickly, response rates can be poor when administered in the absence of the researcher. It can then be difficult to generalise findings as people who bother to return a questionnaire may be psychologically different (e.g. more organised or motivated) to those who don’t. So the results only represent one type of person.

However, one issue with questionnaires is that participants may answer in socially desirable ways, particularly If the responses are not anonymous. This is particularly a problem when researching a sensitive topic such as sexual behaviour or drug taking activity. This questions the validity of the data obtained if it is not their true/honest answer to the questions.

Question 95

what are the 3 types of interviews

listed

Answer 95

1. structured
2. unstructures
3. semi-structured

Question 96

what is a structured interview

Answer 96

identical pre-determined questions are read to participants, with the interviewer writing down the answers.

Question 97

what is a unstructured interview

Answer 97

an informal discussion on a particular topic. Interviewers can explore interesting answers by asking follow-up questions. No preplanning, interviewer responds to answers

Question 98

what is a semi-structured interview

Answer 98

– a combination of structured and unstructured techniques. There is a set of pre-determined questions that all participants are asked, the interviewer can then add in additional questions depending on their answers, can be tailored to the individual

Question 99

designing an interview

Answer 99

When planning an interview decisions need to made about who would make the most appropriate interviewer. Several interpersonal variables may affect this decision:

• Gender, age and ethnicity of the interviewer can affect participants’ answers and what they wish to reveal.
• Personal characteristics – use of formal language, accent and appearance could affect how participants respond to them.

Interviewer training is also an important part of designing interviews. Interviewers need to be able to** listen and learn when to speak and when not to**. They also need to be comfortable with allowing participants time to think about and phrase their answers without jumping in to fill the silence.

Method of data collection also needs to be considered. Interviews can be filmed or recorded, but participants need to be informed of this. Some people would find cameras or tape recorders off-putting. The interviewer could make notes; However, this could be subjective and some information may be missed.
If recorded, a transcript can be made or it can be replayed to check data. Interviews could be analysed using content or thematic analysis

Question 100

evaluation of interviews as a whole

Answer 100

In comparison to questionnaires, the presence of the researcher means that any misunderstood questions can be explained and individual questions may be adapted so they are understood by all participants. Plus interviewee answers can be clarified.

However, the increased presence of the researcher in comparison to questionnaires means that participants may be affected by investigator effects. For example, women may be less willing to talk about sex with male interviewers. Additionally, the presence of the researcher may mean that participants may not answer truthfully and may answer in socially desirable ways, affecting the validity of the data.

Question 101

stengths of a structured interview

Answer 101

• Standardised questions in the same sequence to all participants, more easily replicated to test reliability.
• Limited range of questions - easy to analyse and compare

Question 102

limitations of a structured interview

Answer 102

• May have investigator effects due to researchers working within their own preconceived agenda through set questions.
• Less flexibility: Does not allow for follow up questions/further exploration which can limit the validity of the data.
• Doesn’t tailor to the individual

Question 103

stengths of a unstructured interview

Answer 103

• Reduced investigator effects: the open question schedule means that the investigator does not control the direction of the conversation to meet their own agenda, enhancing validity
• More flexibility: allows for further insight/exploration with follow up questions.

Question 104

limitations of a unstructured interview

Answer 104

• As questions may vary, they are more difficult to compare and analyse and more difficult to replicate.
• Can also be more time consuming and require specialist training.

Question 105

strengtsh of semi-structures interviews

Answer 105

• Not as restricted as a structured interview, can allow for follow up questions and greater insight.

Question 106

limitations of semi-structures interviews

Answer 106

• As questions may vary, they are still more difficult to compare and analyse and replicate than structured interviews.

Question 107

what are case studies

Answer 107

A case study is an in-depth study of a single individual or small group of individuals.
Case studies typically involve a variety of techniques to gain information.
Some of these methods will gain qualitative data such as using interviews, questionnaires, observations – or a combination of all three. Case studies may also involve psychological testing to assess a person’s capabilities and may also produce quantitative data.
They are often longitudinal following the individual/group for a long period of time.

Question 108

strength of case studies

Answer 108

One strength of case studies is that they gain rich, detailed insight into the person or group under investigation. Furthermore, they are important for investigating aspects of human behaviour and experience that cannot be conducted due to practical or ethical reasons e.g., such as an individual with brain damage. This is a strength as they can provide an accurate and exhaustive measure of what the study is hoping to measure.

Question 109

limitations of case studies

Answer 109

One key limitation of case studies is that they lack generalisability This is because in addition to small sample size the subjects of case studies are typically unusual or special in some way, making them of an interest for an investigation. This is a limitation as it questions the usefulness of the findings when trying to apply to a broader population.

 An additional limitation of case studies is that because they are unusual by nature, replication is not possible. This is a limitation as it means that case studies lack reliability

 A further limitation of case studies is that they are subjective. This is because the case study’s researcher may become so involved with the study that they exhibit bias in their interpretation and presentation of the data. Furthermore, case studies may rely on data such as personal accounts from family and friends. This is a limitation as it could question the validity of the data obtained.

Question 110

what is content analysis

Answer 110

a way of analysing qualitative data. It is used to indirectly study behaviour by examining communications e.g., advertisements, books, films, interview transcripts.
For example, researchers have analysed on-line dating profiles to investigate whether men and women are looking for different things in a potential partner or gender stereotypes in TV adverts for children.
It is important for researchers using content analysis to have their research questions formulated, so that they know exactly what their content analysis will focus on. Researchers must familiarise themselves with the data before conducting any analysis,

Question 111

What is content analysis using coding?

Answer 111

This involves converting qualitative data into quantitative data
Coding is an important step in conducting content analysis and involves the researcher developing categories for thedata to be classified. Qualitative data can be extensive in its nature, for example, interview transcripts, and so coding can be helpful in reaching succinct conclusions about the data.

These categories provide a framework to convert qualitative material into quantitative data, which can then be used for further (statistical) analysis.

Question 112

How to carry out Content Analysis using Coding

Answer 112

**Step 1: **Aims and Hypothesis Decide on the aims and hypotheses for the research
**Step 2: **Sample Material Decide on the appropriate sample material that will be used for the content analysis
Step 3: Coding Develop a coding system to categorise the information into meaningful units
**Step 4: **Pilot Study Generally a pilot study may be used to establish reliability in the coding system and make adjustments as necessary
Step 5: Analysis Analyse the data using the coding system interpreting them in regards to the hypothesis e.g., conducting a tally, conversion into graphs.
**Step 6: **Check Reliability Check the reliability of the content analysis by correlating one researchers scores with another’s. (Inter-rater reliability)

Question 113

what is thematic analysis

Answer 113

This is a type of content analysis which also analyses qualitative data but is not worried about quantifying it, focusing instead on identifying themes or idea’s in the data (remains qualitative).
A theme is an idea or notion and can be explicit (e.g., stating that you are feeling depressed) or implicit (for example, using a metaphor of a black cloud for feeling depressed). **Thematic analysis will produce further qualitative data but this will be much more refined. **
For example, a research conducted interviews with several participants about their childhood school experiences. These may run to many pages when in a text form (called a transcript). An example, of what they might be looking for is references to feelings about teachers. References could be coded as teacher positive (TP) or teacher negative (TN) for example.

Question 114

How to carry out Thematic Analysis:

Answer 114

Step 1: Transcription The analysis of qualitative data often starts with collecting the data, and transcribing it (writing it out).

Step 2:** Data Familiarisation** Researcher familiarises themselves with the data – reading and reviewing in detail

Step 3: Reviewing Themes Whilst reviewing data - Generate initial codes and use these to look for themes in the data (these are recurring patterns which run through and link the data). This can be done by colour coding/initialling certain themes as the data is reviewed.

Step 4: Data Saturation Themes may change as more data is analysed and new themes emerge. This means themes are constantly adjusted and data is read and re-read until there is data saturation and no more themes can be identified.

Step 5: Write up When the report is written up the themes are categorised and discussed and the data within each category provides evidence for the themes e.g., through quotes.

Question 115

Difference between content analysis using coding and thematic Analysis

Answer 115

Content Analysis using Coding
- Converts qualitative data to quantitative data
- Coding is decided before analysis/review of the data (it is pre-established)
Thematic analysis
- Data remains in qualitative form
- Codes/themes emerge from the analysis of the data (they are not pre-established)

Question 116

eval of content anaylsis

strengths

Answer 116

Content analysis is particularly helpful when conducting research that would otherwise be considered unethical. Any data that has already been released into the public domain is available for analysis such as newspaper articles, adverts, meaning that explicit consent is not required. Furthermore, it can be used to complement other research methods and can be particularly useful as a longitudinal tool and looking at trends and changes over time.

A strength of both content analysis and thematic analysis is high ecological validity. Much of the analysis that takes place within these research methods are basing their conclusions on observations of real‐life behaviour and written and visual communications in real life contexts. For example, analysis can take place on books people have read or programmes that people have watched on television.

Additionally, since records of these qualitative sources remain, replication of the content/thematic analysis can be conducted. If results were found to be consistent on re‐analysis then they would be said to be reliable, and different individuals can be used to assess inter-rater reliability.

Question 117

weaknesses of content analysis

Answer 117

There is a possibility that content analysis can produce findings that are very subjective. This is because researchers have to make decisions about behaviours/themes to look for and how to categorise the data. Additionally,** the researcher may interpret some things in a completely different manner from how they were intended,** due to their own preconceptions, judgements of biases as it is analysed outside the context in which it occurred. As a result, the validity of the findings can be questioned.

It can be argued to be a description of behaviour rather than explanation of it. As it only describes the data, content analysis cannot extract any deeper meaning or explanation for the data patterns arising, and therefore causality is difficult to establish.

Question 118

what is a pilot study

Answer 118

A pilot study is a small trial run of a study to test any aspects of the design. This allows the researchers to make any improvements or adjustments to design or procedures before the main investigation.

Question 119

why conduct a pilot study

Answer 119

Pilot studies are useful because they allow a researcher to** identify potential issues within their research and modify their procedure if necessary**. This will save time/money in the long run of the research. The few participants who take part in the pilot study can also be asked for their insights into their experience of taking part, e.g. did they guess the aim of the investigation.

Question 120

types of sampling

Answer 120

1. opportunity
2. random
3. stratified
4. systematic
5. volunteer

Question 121

what is an oppurtunity sample

Answer 121

People who are most convenient or most available are recruited, e.g. people walking by in the street, students at a school

Question 122

strengths of an oppurtunity sample

Answer 122

Easiest method and takes less time to locate and recruit the sample than other methods.

Question 123

limitations of oppurtunity sample

Answer 123

Sample is biased and unrepresentative of the target population because some members are excluded, e.g. asking people who walk past you in town on a week day excludes those at work or college.

Question 124

what is random sampling

Answer 124

This is where each member of a population has an equal chance of being selected. E.g. give all members of a population and number and use a computer to randomly select numbers to choose the sample.

Question 125

strengths of random sampling

Answer 125

There is no bias in the selection, increasing the chances of getting a representative sample which can be generalised.

Question 126

limitations of random sampling

Answer 126

Can be time consuming to get a list of all members of a population and allocate them all a number.

Unbiased selection doesn’t guarantee an unbiased sample; all females could be randomly selected by chance. Also not everyone selected will be able to be contacted or will be able to take part.

Question 127

what is a stratified sample

Answer 127

Subgroups (‘strata’) within a population are identified, e.g. males/females, age groups, ethnicities. Participants are randomly selected from each of the strata in proportion to how common they are in the population.

Question 128

strengths of a stratified sample

Answer 128

The sample should be able to be generalised because all the subgroups in the target population are proportionally represented.

As random sampling is used to select participants from the sub-groups of the population it should be free from bias.

Question 129

limiattions of a stratified sample

Answer 129

Detailed knowledge of population characteristics is required which may not be available – there may be hidden subgroups the researcher is not aware of, or who are not accessible.

The dividing of a population into strata and then randomly selecting from each can be time consuming.

Question 130

what is a systematic sample

Answer 130

A predetermined system is used to select participants, e.g. every 10th person from a phonebook.

Question 131

strengths of a systematic sample

Answer 131

Unbiased because participants are selected using an objective system. Therefore the sample should be representative of the population and able to be generalised.

Question 132

limitations of a systematic sample

Answer 132

Not truly unbiased/random (the first person on the list is unable to be selected) unless you select a random number and start with this person.

Question 133

what is a volunteer sample

Answer 133

The researcher advertises for participants, e.g. in a newspaper, on a noticeboard or on the internet. The participants are self-selecting.

Question 134

strengths of a volunteer sample

Answer 134

Quick and easy for the researcher as all they need to do is create the advert and wait for participants to respond.

Question 135

limitations of a volunteer sample

Answer 135

The sample will be biased and unrepresentative as people who like to volunteer for things are likely to be psychologically different to non-volunteers

As volunteers are eager to please the chance of demand characteristics is increased.

Question 136

if asked to write a consent form what should it include

Answer 136

• Enough detail for the person to give informed consent – they should know exactly what will be expected of them, and any potential for psychological or physiological harm.
• They should be informed of their right to withdraw at any point during or after the procedure
• They should be reassured that their results will remain anonymous and confidential
• They should be given the opportunity to ask any questions they may have

Question 137

if asked to write a debrief form what should it include

Answer 137

• They should be thanked for their time
• The full aim of the study should be revealed, and the results expected explained
• They should be reminded of their right to withdraw their results and that their results are confidential
• They should be given the opportunity to ask questions

Question 138

steps in a peer review

Answer 138

1. In the peer review process, a paper is submitted to a journal and evaluated by several reviewers, which are specialists/experts/experienced in the field of study.
2. Elements of the study e.g., methodology, designs and conclusions will be scrutinised and any problems will be identified and discussed. Work is considered in terms of its validity, significance and originality
3. After critiquing the paper the reviewers submit their thoughts to the editor.
4. Then, based on the commentaries from the reviewers, the editor decides whether to publish the paper, make suggestions for additional changes that could lead to publication, or reject the paper.

Question 139

purpose/aims of peer-review

Answer 139

1. To validate the quality and relevance of the research: to ensure that the published research is of a high quality, contributes to the field of research (Is significant wider context) and is accurately presented (e.g., no plagiarism), helping to enhance credibility.
2. To allocate research funding for proposed projects.
3. To suggest amendments/make improvements to the research article

Question 140

strengths of peer review

Answer 140

Can help to establish validity and accuracy of research which contributes to enhancing credibility of psychology as subject.

Question 141

limitations of peer review

Answer 141

• Peer review is subject to bias and there are problems with objectivity. Reviewers find it hard to remain purely objective due to their own education, experience and preconceived notions. Work that is consistent with an existing theory is more likely to be accepted for publication. Peer reviewers may be strongly opposed to the views expressed in the report which could influence their views on the quality of the research. There is also institution bias where reviewers may be influenced by the university the research has come from, e.g. assuming that work from a prestigious institution will be high quality.
• File drawer phenomenon - Peer review tends to favour positive results (where the results support the hypothesis). Many negative findings (where the null hypothesis is accepted) are not published. This may give a false impression of the strength of evidence for a particular theory.
• Burying ground breaking research:** Peer review can act to maintain the status quo and prevent potentially revolutionary research from being published**. This is because science is generally very conservative and resistant to large changes in opinion – what we in psychology would refer to as a paradigm shift.

Question 142

what is reliability

Answer 142

refers to the consistency of research. If a study is repeated using the same method, design and procedure and similar results are obtained then the results are said to be reliable.

Question 143

types of reliability

Answer 143

1. internal
2. external

Question 144

what is internal reliability

Answer 144

is the extent to which a study or test is consistent within itself, e.g. if a word list is being used to test memory then all the words should be equally difficult to remember.

Question 145

what is external reliability

Answer 145

is the extent to which a test measures consistently over time, e.g. an IQ test should give the same results if the same person completes it on more than one occasion.

Question 146

how to asses reliability

Answer 146

• **Split-half method **– measures internal reliability by splitting a test into two and having the same participants do both halves. If the two halves of the test give similar results this indicates that the test has internal reliability.
• Test-retest method – measures external reliability by giving the same test to the same participants on two occasions. If the same result is obtained then reliability is established.

* Inter-rater reliability – a means of assessing whether different observers are viewing and rating behaviour in the same way. A correlational analysis of all the observers’ scores is conducted. A strong positive correlation indicates that they are observing and categorising behaviour consistently.

Question 147

improving reliability

Answer 147

• Reliability can be improved by** developing more consistent forms of measurement** and by **clearly operationalising variables.
  **
• Inter-rater reliability can be improved by training observers in the observation techniques being used and making sure everyone agrees with them. Behaviour categories should be objectively operationalised. This means all observers know exactly what behaviour they are looking for. For example, “aggressive behaviour” is subjective and not operationalised, but “pushing” is objective and operationalised.

Question 148

what is validity

Answer 148

refers to the degree to which a study measures what it claims to and the extent to which findings can be generalised beyond research settings.

Question 149

types of validity

Answer 149

1. internal
2. external

Question 150

internal validity

Answer 150

is the extent to which results are due to the manipulation of the IV and have not been affected by confounding variables such as investigator effects, demand characteristics and bias

Question 151

external validity

Answer 151

is the extent to which the results can be generalised to other settings (ecological validity), other people (population validity) and over time (temporal validity).

Question 152

assessing validity

Answer 152

• Face validity – does the test simply look like it tests what it’s meant to test?
• Concurrent validity – correlating scores on a test with another test which is known to be valid. A strong positive correlation would suggest good concurrent validity.
• **Predictive validity **– look at how well a test predicts future behaviour, e.g. do average GCSE results accurately predict A level results?
• **Temporal validity **– do research findings remain true over time?

Question 153

improving validity

Answer 153

• Internal validity can be improved by reducing investigator effects, minimising demand characteristics (e.g. by hiding the true aim of the investigation), using standardised instructions and a random sample.
• External validity can be improved by setting experiments in more naturalistic settings and ensuring tasks have mundane realism (reflect tasks which occur in real life).

Question 154

technique for checking face validity

Answer 154

One or more judges with relevant expertise assess whether the instrument is appropriate

Question 155

improving face validity

Answer 155

Experts make suggestions based on their expertise as to how the test could be improved

Question 156

technique for checking content validity

Answer 156

Similar to face validity, but more rigorous procedure detailed and systematic examination of all components of test against specific standards

Question 157

technique for checking concurrent validity

Answer 157

Correlation of two sets of test scores one on the established test and one on the new test, taken at the same time and testing for statistically significant coefficient.

Question 158

technique for checking predictive validity

Answer 158

Correlation taken between two sets of scores taken at different points in time and testing for a statistically significant coefficient.

Question 159

improving content validity

Answer 159

Compare and modify the test by comparing against specific standards until it is agreed the content is appropriate

Question 160

improving concurrent validity

Answer 160

If the coefficient isn’t high enough, then the new test would need to be further refined to improve its internal validity

Question 161

improving predictive validity

Answer 161

Could add further predictors so controlling for other factors e.g. Motivation and parental support

Question 162

features of science

Answer 162

To be scientific research should be OBJECTIVE and free from bias. Different people should be able to look at the same data independently and draw exactly the same conclusions. Gathering quantitative data increases objectivity. Variables should be clearly defined and operationalised so it is clear exactly how they were manipulated or measured.
FALSIFICATION is an important part of the scientific process. A theory or hypothesis needs to be able to be empirically tested in order to have credibility. A theory can be accepted as being validated if research evidence supports it but one finding of it not being true leads to its falsification.

For a study to be scientific there should be a MEASURABLE variable. This is difficult in psychology as many of the factors studied are unobservable, e.g. memory. Therefore a valid measurement is needed, e.g. with a memory test. To be scientific a study should be able to be REPLICATED in exactly the same conditions. Therefore research needs to be tightly controlled and free from extraneous variables.

Question 163

paradigm shifts

Kuhn

Answer 163

• This is a paradigm –** a shared set of assumptions about psychology and the methods appropriate to its study**. A paradigm dictates what is studied and researched and the types of questions that are asked.
• Scientists collect data that fits the current paradigm, creating bias where scientific journals publish confirmatory examples of research rather than opposing ones.

Occasionally a paradigm is replaced with a new paradigm which emerges from a minority position. So scientific advancement occurs through paradigm shifts.

Question 164

reporting psychological investigations

Answer 164

1. Title Should be clear, relevant and informative
2. Abstract A summary of the research which allows the reader to get a brief overview of the research so they know if it is worth reading further. Generally consists of two sentences each on the theoretical background (previous research), aims and hypotheses, methodology, results, conclusions and suggestions for future research.
3. Introduction Explains why the study was conducted. General theoretical background, previous research and controversies relating to the area under investigation are covered.
4. Aim(s) Stated clearly and precisely. ‘The aim of this study was to investigate ………….’
5. Hypotheses The alternative and null hypotheses are stated clearly and precisely.
6. Procedure An outline of what was done in enough detail that the study can be replicated. Materials (e.g. questionnaires) are included in appendices. There are several subsections:
   * Design – choice of method (e.g. lab experiment), choice of design (e.g. repeated measures), identification of variables, ethical considerations.
   * Participants – target population, sampling method (e.g. opportunity sampling), details of sample, how participants were allocated to conditions
   * Apparatus/materials – description of any technical equipment used. Materials such as tests/questionnaires etc go in appendices.
   * Standardised procedure – step-by-step procedure allowing replication of the study. May include standardised instructions.
   * Controls – details of controls such as counterbalancing, single- or double-blind procedures, control of extraneous variables.
7. Findings What was found in terms of data collected. Raw data is referenced here and placed in the appendices.
   * Descriptive statistics – measure of central tendency and measure of dispersion and results summarised in an appropriate graph.
   * Inferential statistics – reasons for selecting a particular test. Actual calculations placed in appendices. Outcome of statistical analysis is given with critical values of the test, the significance level and whether it was a one-tailed or two-tailed test. Outcome explained in terms of acceptance and rejection of the alternative and null hypothesis.
8. Discussion Findings are explained in terms of aims and hypotheses and discussed in relation to previous research findings. Limitations such as flawed measurement techniques, poor procedures are outlined and modifications are suggested. Implications and applications of the study are presented and ideas for further research suggested.
9. Conclusion A concise paragraph that summarises key conclusions drawn from the study.
10. References All references cited in the report. Reference lists are created to allow readers to locate original sources themselves. Each citation in a reference list includes various pieces of information including the:
    1) Name of the author(s) 2) Year published 3) Title 4) City published 5) Publisher 6) Pages used

Generally, Harvard Reference List citations follow this format:

• Last name, First Initial. (Year published). Title. City: Publisher, Page(s).

Therefore your text book would be
Flanagan, C. and Berry, D. (2016) A level Psychology. Cheltenham: Illuminate publishing

11. Appendices Contain full instructions given to participants, raw data, calculations, materials

Question 165

what is quantitive data

Answer 165

data is data in the form of numbers or quantities. Anything that measures how much, how long, how many etc. is quantitative. Closed questions gather quantitative data and in an observational study a tally of behavioural categories is quantitative.

Question 166

strengths of quantitive data

Answer 166

that it is easy to analyse using descriptive statistics and statistical tests. Numerical data is also objective – different people will interpret it in the same way.

Question 167

limitations of quantitive data

Answer 167

conclusions drawn may not be valid, as participants and their unique experiences and feelings are simplified to numbers.

Question 168

what is qualitative data

Answer 168

is non-numerical data, usually in the form of words but can also be pictures or images. Qualitative data often concerns what participants think or feel. Open questions in questionnaires and interviews gather qualitative data. In an observation researchers can describe what they see – this would be qualitative.

Question 169

strengths of qualitative data

Answer 169

gives rich detail and may be more valid – participants are not restricted in their answers. It can’t be counted or quantified but can be turned into quantitative data by placing the data in categories and counting the frequency.

Question 170

limitations of of quanlitative data

Answer 170

this analysis is difficult to do without subjectivity and bias.

Question 171

what is primary data

Answer 171

comes directly from first-hand experience. So it is new data collected by the researcher in a study.

Question 172

strengths of primary data

Answer 172

The main strength of this is the control the researcher has. They can design the data collection so it is valid and fits the aims and hypothesis of the study.

Question 173

limitations of primary data

Answer 173

designing a study, recruiting participants, conducting a study and analysing data is time consuming and needs to be funded.

Question 174

what is secondary data

Answer 174

collected for another purpose, e.g. data the researcher collected for a previous study or data collected by another researcher. It also includes Government statistics or data held by an institution such as a hospital.

Question 175

strengths of secondary data

Answer 175

The benefit of this is that it is simpler and cheaper to access pre-existing data.

Question 176

limittaion of secondary data

Answer 176

the data may not exactly fit the needs of the study.

Question 177

what is a meta-analysis

Answer 177

involves combining and analysing data from lots of smaller studies in a particular research area into one large data set. This allows the identification of trends and relationships that wouldn’t be possible from individual smaller studies

Question 178

strengths of a meta-analysis

Answer 178

particularly useful when a number of smaller studies have found contradictory results in order to get a clearer view of the overall picture.

Question 179

what are the measures on cental tendency

Answer 179

1. mean
2. median
3. mode

Question 180

what is the mean

Answer 180

is calculated by adding up all the bits of data and dividing by the number there are

Question 181

eval of the mean

Answer 181

It is the most sensitive measure of central tendency because it takes account of all the values in the data set. However, the mean is easily distorted by extreme values, so may not represent the data as a whole. **The mean is appropriate when there are no extreme scores. **

Question 182

what is the median

Answer 182

is the middle value when the data set is put in numerical order.

Question 183

eval of the median

Answer 183

If there is an even number of bits of data there will be two central values so need to be added together and divided by 2. The median is not affected by extreme values so can be useful when the mean is inappropriate (i.e. when there are extreme scores). However, it isn’t as sensitive as the mean.

Question 184

what is the mode

Answer 184

the value that occurs most frequently

Question 185

eval of the mode

Answer 185

. If two values are equally common the data is bi-modal – both scores are the mode. This is the only measure of central tendency which can be used when the data is in categories. However, it is not useful when there are several modes.

Question 186

definition of measures of central tendency

Answer 186

These are ‘averages’ and are ways of calculating a typical value for a set of data. The average can be calculated in different ways, each one appropriate for a different situation.

Question 187

definition of measures of dispersion

Answer 187

These give information about the variability (spread) of scores within a data set.

Question 188

what are the measures of dispersion

Answer 188

1. range
2. standard deviation

Question 189

the range

Answer 189

calculated by subtracting the lowest value from the highest value in a data set. It is easy to calculate but is affected by extreme values and doesn’t show the distribution of the data (e.g. are most values clustered around the mean with one extreme value).

Question 190

standard deviation

Answer 190

shows the average distance between each piece of data from the mean. The bigger the number, the greater the variability in the data. You won’t be asked to calculate standard deviation in the exam, but may be asked what it shows. A SD does consider all the scores not just highest and lowest so is more accurate. A small standard deviation demonstrates greater consistency and that participants were responding in a similar way (scores clustered around mean). A larger standard deviation demonstrates a greater variability in the data and participants responding differently (scores not clustered around mean)

Question 191

converting a % to a decimal

Answer 191

To convert a percentage to a decimal, remove the % sign and move the decimal point two places to the left.

60% is 60.0. Move the decimal place two points to the left = 0.6

Question 192

converting a decimal to a fraction

Answer 192

Converting a decimal to a fraction
Look at the number of decimal places in your number (number of digits after the point). E.g. 0.6 has one decimal place, 0.81 has two decimal places, and 0.275 has three.

If there is one decimal place you divide by 10. E.g. 6/10
If there are two decimal places you divide by 100. E.g. 81/100
If there are three decimal places you divide by 1000. E.g. 275/1000

Question 193

what does ∝ mean

Answer 193

proportional to

Question 194

what does ≈ mean

Answer 194

weak approximation

Question 195

bar charts

Answer 195

Bar charts allow data in the form of categories to be compared. Categories are placed on the x (horizontal) axis. The y (vertical) axis can show totals, means or percentages. The columns/bars should all be the same width and separated by spaces because the variable on the x-axis is not continuous. Bar charts can display two values together, e.g. male and female consumption of chocolate as shown by gender and age.

Question 196

histograms

Answer 196

These look a bit like bar charts but are different because they are used for continuous data (e.g. scores on a test) rather than that in the form of categories. The scores are placed along the x-axis and the frequency is on the y-axis. There should be no spaces between the bars and their width should be consistent.

Question 197

frequency polygons/line graphs

Answer 197

These are similar to histograms in that the data on the x-axis is continuous. Rather than drawing bars, a line is drawn from where the top of the bar would be in a histogram. A frequency polygon is used when you want to compare two or more frequency distributions on the same graph.

Question 198

scattergrams

Answer 198

Scattergrams display the correlation (relationship) between two co-variables.
One of these co-variables is placed on the X axis, the other is placed on the Y axis.
each point on a scattergram respresnt an individual particpiant

Question 199

features of a normal distribution

Answer 199

• The mean, median and mode are all at the same midpoint.
• When plotted on a graph there is a symmetrical, bell shaped curve.
• The dispersion of scores either side of the midpoint is consistent.

Question 200

a positive skewed distribution

Answer 200

mean is always higher than the median and mode in a positive skew.

Question 201

negatively skewed distribution

Answer 201

distribution is where there are a few low extreme scores. These outliers affect the mean, which is always lower than the median and mode in a negative skew.

Question 202

when to use the sign test

Answer 202

1. Looking for a difference rather than an association. E.g. older people remember more than younger people is a difference
2. Experiment would have used related design (repeated measures or matched pairs)
3. Finally, the data should be nominal (categories)

Question 203

info needed for a sign test

Answer 203

 Calculated value which will be worked out by you
 Critical value which will be provided in a critical value table
 N which is number of scores in the study (Ignoring any 0’s)
 Whether the hypothesis is one tailed (directional) or two tailed (non-directional) in order to determine the level of significance.

Question 204

how to do the sign test

Answer 204

• Step 1: State the hypothesis. Participants will rate their happiness higher in July than in January. This is a directional hypothesis so we require a one-tailed test. (If it was non-directional it would be a two-tailed test).
• Step 2: Record the data and work out the sign. Put each pair of data in a table and add a + or – depending on the difference between the two scores.
• Step 3: Find the calculated value. S is the symbol for the sign test. To calculate S you add up the number of + and add up the number of - and select the smaller value. Here we have 10+ and 3-. So S=3
• Step 4: Find the critical value of S.
   N = total number of scores (ignoring any 0 differences). So in this case N=13 (with one score omitted).
   The hypothesis is directional, so a one-tailed test is used.
  Look at the critical values table. We use the column headed 0.05 for a one-tailed test and the row which begins with our N value. So our critical value is 3.
• Step 5: Is the result significant? If the calculated value is equal to or less than the critical value the result is significant. Calculated value (3) is equal to the critical value (3) so the difference between the two sets of scores is significant. Therefore we can conclude that people are happier in the summer than in winter.

How certain are we? The level of significance we used was 0.05. This is a probability value and means that there is a 0.05 (5%) probability that the results happened by chance and time of year has no effect on happiness. (Sometimes researchers want to be even more certain and use 0.01 – significance at this level means there’s only a 1% probability that the results were due to chance).

Question 205

what are the 3 levels of measuremnet

Answer 205

1. nominal
2. ordinal
3. interval/radio

Question 206

nominal data

Answer 206

Nominal data is data in the form of categories, it is discrete and can only fall in one of the categories

Question 207

ordinal data

Answer 207

Ordinal data is ordered in some way. Ordinal data does not have equal intervals between each unit.

Question 208

interval/ratio data

Answer 208

involves standardised measurement units like time, weight, temperature, distance. These have equal measurement intervals, e.g. 10 seconds is twice as long as 5 seconds. Interval and ratio data are classed together as they apply to the same statistical tests but in theory they are slightly different:
 Interval data doesn’t have a true 0 point (e.g. zero degrees Celsius doesn’t mean there is an absence of temperature.
 Ratio data has an absolute zero point (e.g. someone who scores 0 when remembering a list of 10 words would have remembered none correctly).

Question 209

difference between interval and ratio data

Answer 209

 Interval data doesn’t have a true 0 point (e.g. zero degrees Celsius doesn’t mean there is an absence of temperature.
 Ratio data has an absolute zero point (e.g. someone who scores 0 when remembering a list of 10 words would have remembered none correctly).

Question 210

statistical testing and level of significance

Answer 210

Statistical testing is used to determine whether a difference or association found in a particular study is statistically significant.

A statistically significant result is one where there is a low probability that chance factors were responsible for any observed difference or correlation in the variables tested.
A significant result** allows you to accept your alternative hypothesis** and reject the null hypothesis. It is done so at a level/ probability called as significance level (p-value).

Question 211

what is the level of significance used by psychologists and why

Answer 211

, the 5% level of significance will be used (p≤0.05)

We tend to use this value as it best balances the risk of getting a type 1 and type 2 errors.

Question 212

what is a type 1 error

Answer 212

this is when the null hypothesis is rejected as a result of the statistical analysis but actually the null hypothesis was correct. When p≤0.05 there is a 5% of making this error. If result is significant at p≤0.01 there is only a 1% chance of making a type 1 error. We are likely to make a type 1 error when the p-value is too lenient.

Question 213

what is a type 2 error

Answer 213

this is when the null hypothesis is accepted, but actually the null hypothesis was incorrect. This tends to occur when the p-value is too strict.

Question 214

stats test chart

Answer 214

1st collumn - type of hypothesis. difference, correlation

2nd collumn - level of measurement. nominal, ordinal, interval/ratio [under difference], then ordinal, interval/ratio

3rd collumn - independnet groups. chi-squared, mann-whitney, independent t-test

4th collum- repeated measures. sign test, wilcoxon test, related t-test, spearman’s rho, pearson’s product moment

Question 215

how to tell if calculated value is significant in stats tests

chi-squared, Spearman’s, Pearson’s, independent and related t-tests

Answer 215

if the calculated value is** equal to or greater than the critical value** then the results are significant and the alternative hypothesis is accepted and the null hypothesis is rejected.

Question 216

how to tell if calculated value is significant in stats tests

sign test, Mann-Whitney and Wilcoxon

Answer 216

if the calculated value is equal to or less than the critical value then the results are significant and the alternative hypothesis is accepted and the null hypothesis is rejected.

Question 217

the sign test

what is it used for

Answer 217

• Test of difference
• Related design
• Nominal Data

Question 218

chi-squared

Answer 218

• Test of difference
• Independent/unrelated design
• Nominal data

Question 219

mann-whitney

Answer 219

• Test of difference
• Independent/unrelated design
• Ordinal data

Question 220

wilcoxon

what is it used for

Answer 220

• Test of difference
• Related design
• Ordinal

Question 221

related and unrelated T-tests

Answer 221

• Tests of difference
• Related t-test for related design, unrelated t-test for unrelated design
• Interval data

Question 222

use of spearman’s rho to interpret correlations

Answer 222

The Spearman’s rho (Rs) test can be applied to correlational data which is at least ordinal to find out whether the relationship found is strong enough to be significant.** If Rs is equal to or greater than the critical value the relationship is significant**. (You just looking at the number and ignore + or -. This tells you whether the relationship is positive or negative).

Question 223

use of pearsons product moment to interpret correlations

Answer 223

Another statistical test which is used to analyse correlations is Pearson’s product moment (r) test. This can be applied to correlational data which is at least interval/ratio to find out whether the relationship found is strong enough to be significant. If r is equal to or greater than the critical value the relationship is significant.

Question 225

Design a study to test whether there is a difference in the musical ability of left-handed students and right-handed students. You have access to a sixth form of 200 students. You should:
* Identify the design that you would use
* Explain an appropriate sampling method and justify your choice
* Describe the procedure that you would use, including details of how you would assess musical ability
* Write a suitable debrief for these participants. (12 marks)

example !!!!!!

Answer 225

Design
An independent measures design will be used with a group of left-handed participants and a group of right- handed participants. The IV is whether they are left or right handed and the DV is their musical ability as measured by their score on an A level music exam.
Sampling and justification
Opportunity sampling will be used to recruit participants by studying the students in the sixth form who take A Level music. This sampling method is good because it is a quick and convenient way to obtain participants and is less time consuming for the researcher.
Procedure
Participants will read and sign a consent form so they give informed consent and are aware of their right to withdraw and that their data will remain confidential. The researcher will give each participant a number and record whether they are left or right handed. They will then be given an A level music exam to complete. Their music teacher will mark the exams and their scores recorded. The mean score on the exam for the left- and right-handed students can then be calculated and compared to find out if there is a difference in musical ability of left handed and right-handed students.
Debrief
Dear Participant
Thank you for taking part in their study. We were investigating whether there is a difference in musical ability between left handed and right handed people. We have recorded what hand each of you is dominant in, and have also recorded your score on the music exam to see if there is a difference in the musical ability of left and right handed individuals.
Please be assured that any data collected will be kept confidential and if you may withdraw your data if you would like to.
Do you have any questions? Thank you for your participation.