Research Methods part 2 - Key terms

Question 1

Reliability

Answer 1

The extent to which the findings or research are consistent and replicable.

Question 2

Test re-test reliability

Answer 2

The extent to which the same results will be achieved everytime the test is carried out (Applies to all research methods).
Experiments - if they have standardised instructions, procedures & controls we can replicate them and should get the same results each time.
Questionnaires – if we gave a questionnaire out again, we would expect a ppt to give the same answers again so, we would consider it reliable.

Question 3

Inter-rater reliability

Answer 3

The extent to which the way data is interpreted in a consistent way. This applies when data has been collected by self-report and requires interpretation.
eg, a researcher who is using a questionnaire or interview with open questions may find that the same answers could be interpreted in different ways, producing low reliability. If these differences arose between different researchers, this would be an inter-rater reliability problem.

Question 4

How to achieve inter-rater reliability

Answer 4

Best ways to increase inter-rater reliability:
* Clear and objective methods of collecting data
* Making rating scales as objective as possible to ensure that all researchers are using the same criteria to assess the behaviour and applying the scales in the same way.

Question 5

Intra-rater reliability

Answer 5

whether one researcher is consistent overtime.

Question 6

Inter-observer reliabilty

Answer 6

The extent to which the way data is interpreted in a consistent way.
* Applies when data has been collected by observation and requires interpretation.

eg. in an observation, researchers gave different interpretations of the same actions, this would be **low inter-observer reliability. **

Question 7

How to achieve inter-observer reliability

Answer 7

• Have more 2 or more observeres
• Train them to carry out the observation in the same way to ensure that behavioural categories are clearly operationalised.
• Observe the same behaviour
• Compare results
• If there is 0.8 correlation between observers results (high similarity) then it’s considered a reliable observation.

Question 8

Validity

Answer 8

The extent to which the findings of a study are ‘true’ and ‘accurate’.

Question 9

Internal validity

Answer 9

Are we measuring what we set out the measure?
* If there are EVs, then validity is lowered - because we are no longer testing the effect of the IV on the DV.

Question 10

External validity

Answer 10

Can we accurately generalise? Are the results true beyond the study?

Question 11

Face validity

Answer 11

Is a subjective assessment of whether or not a test appears to measure the behaviour it claims to.
eg. a study measuring aggression amongst teenagers, measures the number of times they swear at each other (swearing is not always linked to aggression, especially in teenagers)

Question 12

Content validity

Answer 12

Is an objective assessment of the items in a test to establish whether or not they all relate to and measure the behaviour in question. Experts assess whether the test is measuring what it set our to do.
eg. A driving test that assesses both theoretical knowledge of traffic rules and practical driving skills: This ensures the test covers all necessary components to be a safe driver.

Question 13

Concurrent validity

Answer 13

Is a comparison between two tests of a particular behaviour. One test has already been established as a valid measure of the behaviour, and the other test is the new one. If the results from both significantly correlate, then the new test is valid.
eg. Comparing a new IQ test to a well established IQ test. The ppt should score similar on both to show that the new one is a valid measure.

Question 14

Predictive validity

Answer 14

Refers to how well a test predicts future behaviour. eg. do your mock exams predict your actual results? Are they vaild?

Question 15

External validity

Population validity

Answer 15

How well can we generalise from the sample to the population we want it to represent. Is the behaviour true for others? Is our sample representative?

Question 16

External validity

Ecological validity

Answer 16

How well can we generalise from the study to how people behave in everyday life. Is the behaviour true in other settings? Does the study environment or task represent real life?

Question 17

External validity

Temporal validity

Answer 17

Would the findings of an older study still be true today, is the ppts behaviour in the study still generalisable to today’s society?

Question 18

Extraneous variable

Answer 18

A variable which could affect the DV and therefore should be identified and controlled before you begin the research.

Question 19

Cofounding Variable

Answer 19

A variable that has affected the DV and so would be mentioned after the study has been conducted.

Question 20

Control variables

Answer 20

• This is where psychologists keep everything the same (except the IV) across the different conditions and for all ppts.
• Ensures that the IV has affected the DV and nothing else.
• Ensures that the research can be consistently replicated in the same way for all ppts.
• Increases validity and reliability of the research

Question 21

Extraneous Variables

Participant variables

Answer 21

Demand characteristics: ppt guesses the aim of the study, changes their behaviour to please the researcher
“Screw you” effect: ppt guesses the aim of the study, changes their behaviour to sabotage the research
Individual differences: Differences between ppts, such as personality, IQ, mental health etc which could affect the DV.

Question 22

Extraneous Variables

Situational variables

Answer 22

Factors in the environment that can unintentionally affect the results of a study.
Eg.
Noise
Temperature
Distractions

Question 23

Extraneous variables

Experimenter variables

Answer 23

Experimenter effects: elements of the experimenter’s appearance or behaviour affects the behaviour of ppts

Experimenter bias: the experimenter interprets behaviour or data in a way that is biased to support a particular outcome.
* Or the experimenter selects ppts who are more likely to behave in a way that will support a certain outcome.

Question 24

Types of Experimenter bias

Answer 24

**Non-verbal communication: **Researcher can communicate their feelings about what they are observing. Can also encourage ppts behaviour to support their own hypothesis, sometimes without even realizing that they are doing this.
Physical characteristics: The appearance of the researcher will influence the behavioral response of the participants. eg. gender, outfit
Bias in collection/interpretation: collecting and interpreting the data in a biased way.
Bias in selection of ppts: could select ppts who they know would be more likely to behave in a specific way or who may be easier to work with.

Question 25

# Extraneous variables Task variables

Answer 25

Aspects of the instructions, materials and the design are not kept constant across the different conditions. * Or the way the tasks have been set up affect the results eg. order of tasks

Question 26

Techniques to control extraneous variables

Answer 26

**Standardised instructions/procedure**: Carrying out the experiment/study in the same way with the same instructions for all ppts = reduces situational & task variables **Counterbalancing**: Varying the order that the ppts do the tasks or the conditions of the experiment (ABBA) = reduces order & practice effects **Experimental design**: Repeated measures design can reduce ppt variables Independent measures & matched pairs can reduce task variables **Single blind:** Ppt doesn't know what condition they are in > reduces demand characteristics. **Double blind:** Ppt and researcher does not know what condition they are in > reduces demand characteristics and experimenter bias **Pilot Studies:** A study on a small scale performed prior to the main study (pre-study). > This reduces task variables

Question 27

Mundane Realism

Answer 27

The extent to which the task represents a real-world situation. eg. Would we behave this way in everyday life. Similar to ecological validity. If the experiment lacks mundane realism, then it will be low in ecological validity. **Low mundane realism** = task is artificial **Ecological validity** = can't generalise from the findings.

Question 28

Participant Observation

Answer 28

The observer participates in the behaviour they are observing (but can be overt or covert)

Question 29

Non-participant observation

Answer 29

The observer does not take part in the behaviour they are observing (but can be overt or covert)

Question 30

Structured observation

Answer 30

Uses behavioural categories and a coding frame to collect data (event sampling/time sampling)

Question 31

Unstructured observation

Answer 31

Collects all data that is relevant with no pre-planned behavioural categories.

Question 32

Controlled observation

Answer 32

Participants are given a task and then observed doing the task

Question 33

Naturalistic observation

Answer 33

participants are observed behaving naturally with no manipulation from researchers

Question 34

Covert observation

Answer 34

Under-cover > participants don't know that they are being observed

Question 35

Overt observation

Answer 35

Participants know they are being observed.

Question 36

# Data collection techniques for controlled/structured observations Main sampling methods

Answer 36

**Event sampling** - observer decides in advance what types of events is of interest and records all occurrences. All other types of behaviour are ignored. **Time sampling** - observer decides in advance that observation will take place only during specific time periods and records the occurrence of the specified behaviour that period only. eg. every hour, 1 hour per day

Question 37

# Observations Evaluation of event sampling

Answer 37

**Strengths** - Behaviour won't be missed as every time specific behaviours occur, they are recorded. **Weaknesses** - If too many observations happen at once, it may be difficult to record everything.

Question 38

# Observations Evaluation of time sampling

Answer 38

**Strengths** - The observer has time to record what they have seen as they aren't observing for the whole time they are present. **Weaknesses** - some behaviours will be missed if they are outside the designated time intervals. Therefore, observations may not be representative.

Question 39

Correlations

Answer 39

Shows the relationship between two or more variables. It cannot show a cause-effect relationship. There may be an intervening variable.

Question 40

Difference between correlations and experiments

Answer 40

* In an experiment we are looking for a difference in behaviour across the different conditions – so it is a test of difference. * Whereas in a correlation we are looking for **relationships between variables**. * There will be **no IV and DV** (just co-variables: variable 1 and variable 2) * There will be **no experimental design** in correlations * The hypothesis for correlations will not state that the IV will/will not affect the DV – just that there will be a **relationship** between the two variables * Data will be shown on a** scatter graph** rather than a bar chart. * **Quantitative data **is required for a correlation. Participants will need a score on both the variables you are investigating the relationship between.

Question 41

Positive correlation

Answer 41

As the value of variable 1 increases so does variable 2 (although not necessarily at the same rate) Both variables go in the same direction. So they can also both be decreasing. E.g. As ice cream sales increase, so do burglaries.

Question 42

Negative correlation

Answer 42

As the value of variable 1 increases the value of variable 2 decrease. eg. The more school you skip the worse your grades will be.

Question 43

How to write Correlation Hypothesis

Answer 43

* **One-tailed (directional)** > “there is a positive relationship/correlation between age and beauty” * **Two-tailed (non-directional)** > “there is a relationship/correlation between age and beauty” * **Null hypothesis** > “there is no relationship/correlation between age and beauty”

Question 44

Strengths of correlations

Answer 44

* Can test relationships between naturally occurring variables that would be difficult or unethical to measure experimentally. * Good way of indicating trends which may lead to further research being carried out * Can establish a cause-effect relationship * Useful to establish the **reliability** of a questionnaire (split-halves method), an observation (inter-rater reliability) or an experiment (test-retest reliability)

Question 45

Weaknesses of correlations

Answer 45

* Because the variables in a correlation are naturally occurring, the psychologist may find it difficult to control extraneous variables. * Correlation studies cannot produce cause-effect relationships – which means we may be unsure which variable was the cause and which was the effect or if the effect was caused by an intervening variable.