Research Methods Flashcards
(81 cards)
1
Q
Advantage of Naturalistic Observations.
A
High Ecological validity.
Disadvantages:
- poor control of extraneous variables so can lead to reduced internal validity.
- observe bias - only wrote down what they think in necessary (also can reduce internal validity) this can be reduced by using more than one observer.
- no IV
- Observing something in a natural environment.
- inter-observer reliability - More than one observer compare using correlation.
2
Q
There can also be:
A
Participant and non-participant observation.
3
Q
Unstructured Observations.
A
No system - record all relevant behaviour
- Too much to record
- Behaviours recorded will be the most visible; may not be the most important
4
Q
Structured Observation.
A
Observers have to avoid being overloaded so focus on:
1) Event sampling
2) Time sampling
To avoid making immediate judgements observers now tend to use videos to record data.
5
Q
Controlled Observations.
A
- There is some experimenter control.
- The participants know they are being observed which may affect results.
- Ainsworth and Bell’s strange situation is an example of a controlled observational study.
6
Q
Observations.
A
- when conducting an observation you must categorise the specific behaviours you aim to observe.
- so if you are studying aggression you would categorise the behaviours by stating that aggression would be measured by hits or kick etc OR you could RATE the behaviour by counting the kicks and hits.
- controlled observations are very much like experiments but more detailed info can be obtained.
BUT - artificial conditions can influence behaviour and there are the problems of investigator effects and means characteristics.
7
Q
Naturalistic Observation.
A
- behaviour is studied in a naturalistic setting - no interference from investigator.
Controlled Observation - behaviour is studied under controlled conditions.
8
Q
Observations.
A
- Participants are observed engaging in the behaviours being studied and the observations are recorded.
9
Q
Weakness of Natural Experiments.
A
Lack of randomisation so the sample may not be able to be generalise to the wider population. Also there are ethical concerns which include taking advantage of people.
10
Q
Advantages of Natural Experiments:
A
1) Participants are unaware that they are taking part in an experiment so behaviour tends to be realistic - making findings more reliable.
2) PERMITS the study of variables that it would be unethical to manipulate.
11
Q
Natural Experiments.
A
- Makes use of a naturally occurring event. THE INDEPENDENT VARIABLE CHANGES NATURALLY - no MANIPULATION.
- In St Helena people didn’t receive TV until 1995 so psychologists were able to compare children’s level of aggression before the introduction of TVs their aggression afterwards.
- IV occurs naturally and can’t be manipulated.
12
Q
Field Experiments.
A
- Take place in natural settings but the experimenter still manipulates the IV. Higher in ECOLOGICAL VALIDITY.
- But low in INTERNAL VALIDITY because it is hard to control extraneous variables which may affect the outcome and also participants may guess that they are taking part in an experiment and of this happens their behaviour wouldn’t reflect how they would normally act.
- Higher in ecological validity - external validity.
13
Q
Weaknesses of LAB experiments.
A
1) Artificial - so they lacking ecological validity. This means that the findings may not reflect what would happen in real life situations.
2) Demand Characteristics may lower validity - people may use clues in the environment to guess what is expected of the, and then would act accordingly.
3) Ethical Issues - In LAB experiments people may feel as if it is difficult to withdraw and discontinue their participation as it is often a more pressured environment.
14
Q
Strengths of LAB Experiments.
A
- High levels of control means that experiments are high in internal validity. It is easy to see that the IV is having an affect on the DV.
- High levels of control also means that it is easy to repeat the experiment I’m exactly the same way to assess the reliability of the study (high reliability if we get the same result)
- Internal Validity - control, are we testing what we set out to test,
- External - generalise our findings out of the research setting.
- Ecological Validity - can we generalise findings to other places/settings.
- Mundane Realism - reflex the real world.
- Inter-rater reliability.
15
Q
Volunteer sample.
A
Relying solely on volunteers to make up the sample.
Advantage:
- Access to a variety of participants - more representative less biased.
Disadvantages:
- The sample is biased Volunteer Bias, as participants may be more motivated and/or have more time on their hands.
16
Q
Opportunity Sample.
A
Selecting people who are most easily available at the time of study.
Advantages:
- Easiest method as you use the first participants you find - less time consuming than the other sampling techniques.
Disadvantages:
- Biased as the sample comes from only a small part of the target population.
17
Q
Random Sampling.
A
- Using a random technique so that every member of the target population has an equal chance of being selected.
Advantages:
- All members of the target population have an equal chance of being selected - so this technique is unbiased.
Disadvantages:
- Does not guarantee a representative sample (area bias and so on) so can be biased.
18
Q
How to get a sample.
A
Random Sampling:
- selecting participants completely at random - the best method - computer generated.
Opportunity Sampling:
- using people who are readily available.
Volunteer Sampling:
- asking people to help you by taking part in your study - usually through advertising.
19
Q
Selection of Participants and Sampling Techniques.
A
When conducting our research we often want results to generalise to the wider population so we need a REPRESENTATIVE sample.
- Some studies have only used students so there is sampling bias.
- Volunteer, opportunity, random sample and demand characteristics.
20
Q
To overcome order effects counterbalancing should be employed.
A
AB/BA A=Alcohol/B=No-alcohol
Half the participants do condition B first then condition A.
AB = artificially High/Low
BA = artificially High/Low
21
Q
Matched Pairs Design.
A
Advantages:
- Controls some participant variable which reduces the effects of individual differences.
Disadvantages:
- It is very difficult to control/match all variables because you rarely find two individuals who are exactly the same.
22
Q
Repeated Measures Design.
A
Advantage:
- Controls ALL individual differences and requires fewer participants.
Disadvantages:
- There can be order effects which would lower the internal validity.
23
Q
Independent Groups Design.
A
Advantages:
- No order effects, no loss of participants as they are split into different groups.
Disadvantages:
- Individual differences (like natural ability) may affect results.
24
Q
Experimental Design. (Different from research methods).
A
Experimental design if an experiment has TWO conditions (parts)
- Independent Groups Design - different participants in each group - randomly assigned.
- Matched Pairs Design - Different participants in each condition but they are matched according to age/sex etc -‘to try and make the test fair.
- Repeated Measures Design - Participants do both conditions.
25
Operationalisation of Variables Including independent and dependent variables.
- Before we can measure the value of a variable it must first be operationalised.
- This means it must be defined in terms of something that can be measured.
- Making your variables so specific that another researcher could copy you I'm exactly the same way.
- We must Operationalise the Independent variable so the other researchers can see how we have measured it. Be specific.
- So if we are testing the effect of the time of day we revise on learning we would.
- Operationalise the IV by stating that the IV is whether the participants learn at ten in the morning or ten in the evening.
- If we are testing whether students who revise have better exam results we would.
- Operationalise the IV by stating we would use students who revise for 4 hours a week versus those who don't revise.
26
Two Conditions.
If an experiment has two conditions, the 'normal' condition is called the control condition and the other is called the experimental condition.
So, if we are testing if caffeine increases concentration, the control contrition would be the condition without caffeine.
27
Other Variables.
Experiments can sometimes include other variables that are 'extra' and can be hard to control. These may also affect the outcome (the DV).
These are called extraneous variables light, noise, temperature, differences in age/ability etc.
To ensure high validity, extraneous variables HAVE to be constant for ALL participants OR have to be eliminated.
28
Variables.
- Independent Variable, the variable that the experimenter manipulates. Assumed to affect the DV.
- Dependent Variable. The variable that you think will be affected by the IV (DV is dependent on the IV) The variable that is measured.
- Participants remember more words before lunch then after lunch.
29
Variables.
- In an experiment the relationship between two things is investigated. E.g. We may study the relationship between revision and exam success.
- These two things are collectively known as variable.
30
Experimental/Alternative hypothesis. The
- Experimental/Alternative hypothesis may be one tailed (directional) or two tailed (non-directional).
- A directional hypothesis will predict the effect of the IV on the DV
- A non directional hypothesis will state that there will be an effect but won't state the direction.
31
What is the Null Hypothesis?
This simply states that the independent variable will not affect the dependent variable. You will have to believe that the null hypothesis is true until you have finished your research and you analyse your findings.
E.g. Loud noise will not affect a persons ability to remember information read in a textbook.
- Null is true until you prove yours is Null = statement of no effect.
32
What is an Experimental Hypothesis?
- A clear guess. A precise, testable statement.
E.g. If I am studying whether noise affects a persons ability to study, my hypothesis might be that - loud noise will affect a persons ability to remember information read in a text book.
-We use hypotheses with ALL research methods. With anything other than an experiment the experimental hypothesis is called the Alternative Hypothesis.
33
Experimental Method.
- Laboratory experiments are conducted in artificial settings and involve high levels of control.
- This method involves the Independent Variable (manipulate) and the Dependent Variable (measure)
34
Correlational analysis. Weaknesses.
- Doesn't establish cause and effect as direction of causality cannot be established.
- Other variables may be operating which could affect the results therefore limiting the validity of the research.
35
Correlational analysis.
Looking for a relationship between two variables.
Example: is there a relationship between watching to much television and more aggressive behaviour. OR is there a relationship between hair colour and IQ score.
36
Case Studies. Disadvantages.
1) What is true for one individual may be true for others. (Cannot make generalisations based on the findings) So any conclusions drawn will be questionable.
2) Therapist may often only report a small amount of data (to support their theory).
- individual differences.
37
Case Studies. Advantages.
Good quality data that can be used to challenge theories and provide insights into future research.
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Case Studies.
A detailed, qualitative, account of one or two individuals and their experiences.
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1) Demand Characteristics
| 2) Investigator effects
1) Cues in the environment to what the aims of the experiment.
2) Way investigators behaviour and expectations (anything that involves the investigator)
40
Pilot Studies.
1) Allow researchers to check out standardised procedures.
2) Help to ensure that participants know what is expected of them.
3) Can help researchers decide how many people should be involved in the study.
4) Can highlight anything that needs to be changed.
Mini research to make the real study valid.
41
Why are pilot studies conducted?
To make sure everything is OK before testing it. Get feed back to make changes before doing it for real.
42
Controlled Observation.
Advantages:
- can manipulate multiple variables to observe effects
Disadvantages:
- observer bias, demand characteristics
(Demand characteristics when participants figure out what's going on using clues in the environment. Find what's expected of them)
43
Demand Characteristics.
- Cues in the environment (aspects of the study) that participants use to try and work out what is expected of them.
- The experimenter can gain in for about the demand characteristics in any situation by asking participants to write about what they thought the experiment was about interpreter behaviour
44
Investigator Effects.
- Expectations and behaviour of the investigator can affect the participants behaviour.
- Consequently they can interpret results in a way which is biased (reducing the internal validity)
45
Dealing with Investigator Effect.
Single Blind Design:
- Participant is unaware of the true aims of the study.
Double Blind Design:
- Avoids investigators affects. Both unaware of the true aims.
(Research and Participants)
- Employ a researcher in how they'd do this.
46
Validity.
Internal Validity:
- Control
External Validity:
- Can the finding be generalised in different situations
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Internal Validity.
- the experiment tests what it claims to be testing. Internal validity can be compromised by demand characteristics, investigator effects, extraneous variables etc.
- the higher the level of control - the better the internal validity.
48
Reliability.
- to be considered for publication an experiment should be high in validity and reliability.
- consistency - how consistence is the result.
49
External Reliability.
- the same results are achieved whenever the experiment is repeated - to test this we use the TEST-RETEST METHOD.
- whenever they're consistent throughout time. (test retest method high in external reliability)
50
Internal Reliability.
This measures the extent to which a test or procedure is consistent within itself, i.e. Questionnaire items or questions in an interview should all be measuring the same thing.
51
Testing Internal Reliability.
Split-half.
Odd/Even Or Top/Bottom
- Compares a participants performance on two halves of a test or questionnaires - there should be a close correlation between scores on both halves of the test. Questions in both halves should be of equal quality for good internal reliability.
- tears should be the same, testing consistency.
52
Ethics.
All researchers must adhere to the British Psychological society (BPS) code of Ethics.
53
Why is ethical guidelines important?
- Ethics are considered from cost-benefit analysis.
- We may justify some unethical procedures if the ultimate outcome is good for human kind (like animal testing for medicinal reasons).
- Put in place to protect participants.
- Some are allowed if the costs out weight the benefits.
54
The key ethical issues that have to be considered are:
1) The use of deception. (Deception is used to get an honest answer).
2) Informed consent (being informed about the nature of the experiment and you rights).
3) The protection of participants from harm.
4) Confidentiality.
55
Deception.
- Sometimes in research Deception is necessary.
- Deception can be justified if the issue being studied can only be explored in this way and if the study is important.
- All deceived participants must be fully debriefed at the end of the study and have a right to withdraw their data.
56
Informed Consent.
Informed consent is not possible when:
1) Children/Participants are limited in their understanding
2) When deception is necessary
3) In field experiments
57
Other ways to obtain consent:
1) Presumptive consent - gaining views on what is acceptable from the general public. (Ask the general public/people you're targeting if they'd do it and then assume the people your studying on that they'd be okay with it.)
2) Prior GENERAL consent.
3) Another way to gain consent is AFTER the experiment by debriefing and allowing the participants to withhold their data, should they so wish.
58
Protection from harm.
- This is vital in any study.
- Harm can be physical or psychological.
- Psychological harm can be difficult to measure. In studies where there may be embarrassment or distress there should always be confidentiality.
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Conformity.
- Researchers aiming to study conformity drew three lines (A,B and C) of different lengths on a board. Participants were asked to state aloud which line was the same size as line X.
- Eight confederates (friends) of the researcher who were in on the study all stated that line A was the same length, the one true participant copied them and gave the same answer even though it was obviously wrong.
- No information consent.
- Could harm participants.
- Deception.
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1) Explain any ethical issues that could have arisen in the study.
1) They were deceived and could have been harmed.
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2) Explain how the researchers could justify the ethical issues and minimise any risk to the participants.
2) Used deception because it couldn't be justified any other way.
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Analysing Quantitative Data.
- Data in numerical form.
| - Measures of central tendency and dispersion.
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Measures of central tendency.
- Mean (most often)
- Median (➕ up ➗ how many) }average
- Mode
- ie finding a 'typical' value from the middle of the data.
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You need to be able to:
- explain how to calculate the mean, median and mode.
| - state the strengths and weaknesses of mean, median and mode.
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Mean.
Precise - considers every score. If there is an extreme number don't use mean. Eg. 17 17 16 (250) - extreme value.
Advantage:
- More sensitive than the median, because it makes use of all the values of the data.
Disadvantages:
- It can be representatives if there is an extreme value.
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Median.
Advantages:
- It is not affected by extreme scores.
Disadvantages:
- It is less sensitive than the mean, as it does not take into account all of the values.
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Mode.
Advantages:
- It is useful when the data are in categories, such as the number of babies who are securely attached.
Disadvantages:
- It is not a useful way of describing data when there are several modes.
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Measures of Dispersion.
- Measures of "spread"
| - This looks at how "spread out" the data are.
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Range and Standard Deviation.
- The range is the difference between the highest and lowest numbers. For example,
- 3, 5, 8, 8, 9, 10, 12, 12, 13, 15
Mean: 9.5 Range:12 (3 to 15)
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Standard Deviation.
- Standard deviation tells us the average distance of each score from the mean.
- 68% data is normally within 1sd each side of the mean.
- 95% within 2sd.
- Almost all is within 3sd.
- Don't need to work this out.
It's more precise than the mean how much of the data is spread from the mean.
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Range.
Advantages:
- Quick and easy to calculate.
Disadvantages:
- Affected by extreme values (outliners).
- Does not take into account all the values.
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Standard Deviation.
Advantage:
- More precise measure of dispersion because all values are taken into account.
Disadvantages:
- Much harder to calculate than the range.
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Bar Chart.
- Used to represent data which is in categories
- Columns do not touch and have equal width and spacing
Examples:
- Differences in males/females on a spatial task
- Score on a depression scale before and after treatment.
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Frequency Polygon.
- Can be used as an alternative to the histogram.
- Lines show where mid-points of each column on a histogram would reach.
- Particularly useful for comparing two or more conditions simultaneously.
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Scattergram.
- Used for measuring the relationship between two variables.
| - The pattern of plotted points reveals different types of correlations, e.g., positive, negative or no relationship.
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Correlations.
- Correlations can be positive (they rise together) or negative (as one variable increases the other decreases)
- The extent to which the variables are related is measured by a correlation coefficient.
It indicates the direction and the strength of the relationship.
- Positive correlation is +1.0
- Negative is -1.0
77
Content analysis.
Way to answer qualitative data.
- Will attempt to classify and describe any written or spoken communications (TV, Radio, Adverts, Posters etc).
- Will use categories and codes to turn qualitative data into quantitative data.
78
Content analysis involves the researchers:
1) Making a Hypothesis
2) Decide which sources of information to use (to conduct the research)
3) Look for suitable categories into which information can be placed. Look for categories to emerge from the data, bottom up or decide categories before you conduct the research, top down.
4) Two or more judges should assign the information to certain categories to ensure reliability.
5) Count how many times information relates to each category.
6) Turn into Qualitative data.
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Qualitative.
Refers to quality data that isn't normally statistically analysed. Qualitative = open. Example, what's your opinion on reality TV?
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Research is done to try to prove a theory.
Starts with an aim. An aim will tell the reader what the research aimed to find out.
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Quantitative.
Refers to a large amount of data that is easily compared and statistically analysed. Quantitative = closed. Example, how old are you?
