• Shuffle
    Toggle On
    Toggle Off
  • Alphabetize
    Toggle On
    Toggle Off
  • Front First
    Toggle On
    Toggle Off
  • Both Sides
    Toggle On
    Toggle Off
  • Read
    Toggle On
    Toggle Off

Card Range To Study



Play button


Play button




Click to flip

Use LEFT and RIGHT arrow keys to navigate between flashcards;

Use UP and DOWN arrow keys to flip the card;

H to show hint;

A reads text to speech;

67 Cards in this Set

  • Front
  • Back
  • 3rd side (hint)
What are the 4 types of experiments & describe?

1. Laboratory

- high level of control over IV

- eliminates confounding variables

- IV manipulated to observe affect on DV.

2. Field

- natural environment of participant

- experimenter has control of IV

- participants may not know they are being studied.

3. Natural Experiment

- IV not manipulated, occurs naturally

- researcher has no control of allocation of participants.


- IV based on existing difference between people (no manipulation)

- resembles lab or field experiment.

- typically carefully planned unlike natural experiments.

Difference between a field experiment and a natural experiment?

Field - Experimenter has control over the IV


Natural - IV occurs naturally, not directly manipulated.

Evaluation of Lab Experiments


1. Control Over Variables

- Easy to control potential confounding variables (unlike natural & field)

- Leads to cause and effect easily being established

2. Replicability

- Easily repeated by others to see if they obtain similar results = reliable (unlike field & natural)


3. Artificial

- high levels of control = different from real life situations

-difficult to generalise = lacks ecological validity (unlike field & natural)

4. Demand Characteristics

-Participants try to work out aims and act accordingly

- They may try to help or deliberately confound the results.

1. Control

2. Replicability

3. Artificial

4. Demand Characteristics

Evaluation of Field Experiments


1. Improved Ecological Validity

- natural setting = can be generalised to real life situations (unlike lab)

2. Reduction of Demand Characteristics

- Participants unaware they are taking part in study = minimised DC


3. Less Control

- difficult to control extraneous variables = decreased internal validity

- difficult to replicate

- difficult to establish cause and effect

4. Time Consuming

-waiting process for condition to occur

1. Ecological Validity

2. Reduced Demand Characteristics

3. Less Control

4. Time Consuming

Evaluation of Natural Experiments


1.Reduction of Demand Characteristics

- Participants unaware they are taking part in study = minimised DC (unlike lab)

2. Lack of Direct Intervention

- Researcher doesn't directly intervene

= more opportunity to gain insight into real life behaviour


3. Loss of Control

- IV not directly controlled by researcher

=reduces likelihood of cause and effect being established b/c too many confounding variables.

4. Replication Impossible

- situation occurs rarely

-difficult to check external validity of the findings

1. Reduction of DC

2. Lack of Direct Intervention

3. Loss of Control

4 Replication Impossible

Evaluation of Quasi-Experiments


1. Replicability

- often carefully planned

- highly controlled

2. Useful to make comparisons between types of people

- where it is impossible or impractical to manipulate the variables


3. Confounding Variables

- can't randomly allocate participants

- cant establish causality

4. Demand Characteristics

- carried out in a lab

= leads to DC

1. Replicability

2. Useful to make comparisons between...

3. Confounding Variables

4. Demand Characteristics

What are the 6 types of observational techniques & describe?

1. Naturalistic Observation

- Behaviour observed in natural context.

-No direct manipulation of variables.

2. Controlled Observation

- Researcher attempts to control certain variables.

- Observation conducted in a lab.

3. Covert

- Participants unaware they are being observed

4. Overt

- Participants know they are being observed.

5. Participant

- Observer becomes part of the group they are studying.

6. Non-participant

- Observer remains separate from the group they are observing.

Evaluation of Naturalistic Observations


1. High Ecological Validity

- participants unaware = natural behaviour

- less chance of demand characteristics

2. Study behaviour where can't manipulate variables

- Data can be collected from participants who cannot be tested in other ways

(3. Fewer Ethical Issue)


4. Observer Bias

-Different observers may see different things = low-inter reliability.

5. Lack of Control

- No control of variable = replication is impossible

- Hard to establish external validity & more extraneous variables

1. High Ecological Validity

2. Study behaviour where can't manipulation

4. Observer Bias

5. Lack of Control

Evaluation of Controlled Observations


1. Time Saving

- Possible to manipulate situation = you don't have to wait for desired behaviour to be shown.

2. Preliminary Research

- develop new hypothesis for future investigations.


3. Low Ecological Validity

- participants behaviour may change because they know they are being watched.

4. Observer Bias

- Different observers may see different things = low-inter reliability.

1. Time Saving

2. Preliminary Research

3. Low Ecological Validity

4.Observer Bias

Evaluation of Covert Observation


1. High Ecological Validity

-Behaviour is more natural = pp's unaware they are being watched


2. Ethics may be questionable

- invasion of privacy

-lack of informed of consent

1. High Ecological Validity

2. Ethics may be questionable

Evaluation of Overt Observation


1. More ethical than covert

- can informed consent


2. Reduced Ecological Validity

-pp's now they are being watched = may lead to participant reactivity.

1. More ethical than covert

2. Reduced Ecological Validity

Evaluation of Participant Observation


1. Special Insight

- gain special insight into the behaviour =increasing validity of findings


2. Observer Bias

1. Special Insight

2. Observer Bias

Evaluation of Non-participant Observation


1. Objective

- Observer more likely to be objective.


2. Data lacks richness

1. objective2. data lacks objectiveness
What is a questionnaire?

- structured set of questions

- asks a large sample for views & opinions

- questions can be closed or open

Evaluation of Questionares


1. More Truthful Responses

- People more willing to express themselves (than face to face interviews)

- they remain anonymous = more reliable data

2. Simplicity

- can be carried out w/ minimum of training accessing a large group of pp's


3. Problems w/ the wording of the questions

- may influence the respons

- not a true reflection of respondent's views.

4. Biased Samples

- response rate is very low

- sample is not representative of the population

1. More Truthful Responses

2. Simplicity

3. Problems w/ the wording of the questions

4. Biased Samples

What is an interview and what types are there?

- A face to face situation where an interviewer asks a series of questions to the respondent (structured), or created in response to answers (unstructured), or mix of 2 types (semi structured)

Evaluation of Structured Interviews


1. Replicable

- Standardised q's = replicable

- Answers from different pp's can be easily compared (in comparison to unstructured interviews).

2. Misunderstood questions can be explained

- improves validity


3. Social Desirability

- interviewees may give biased answers they think will give a favourable impression.

4. Requires Skilled Personnel

- researchers need to be trained in effective interviewing skills (not need in questionnaires).

1. Replicable

2. Misunderstood questions can be explained

3. Social Desirability

4. Requires Skilled Personnel

Evaluation of Unstructured Interviews


1. Lots of 'rich' data

- w/ use of open ended questions about personal issues

2. Flexibilty

- enables complex issues to be explored in further depth by tailoring questions.


3. Requires Skilled Personnel

- researchers need to be trained in effective interviewing skills (not need in questionnaires).

4. More difficult to analyse the data

- lack of standardised q's

-large amount of data gathered.

1. Lots of 'rich' data2. Flexibilty3. Social Desirability4. More difficult to analyse the data

What is a correlational analysis
An investigation that measures the extent of the relationship between two co-variables

3 Types of Correlation & description

Positive Correlation

- co-variables increase or decrease together

Negative Correlation

- 1 variable increases while 1 decreases

Zero Correlation

- no relationship

What is a correlation coefficient?

A number that tells us how closely the co-variables are related.

- The stronger the correlation the closer to the correlation coefficient to +1 or -1.

Evaluation of Correlations


1. They allow researchers to investigate situations that can't be done experimentally (when practically impossible to manipulate the IV).

2. Preliminary Research

- Can indicate the trends that lead to further research using experimental means to establish causal links.


3.Cannot establish cause and effect

- Only tells us that variables are related not which co-variable is causing the other

4. Third Variable Problem

- There may be other unknown variables that explain why co-variables are linked

1.Allows researchers to investigate situations that can't be done experimentally.

2. Preliminary Research

3. Cannot establish cause and effect

4. Third Variable Problem

Difference between correlations and experiments.

Correlation - simply measured, no deliberate change/ Experiments - deliberately changes IV to see effect on DV

Correlations - relationships are measured & cause and effect not established/ Experiments - cause & effect can be established.

What is the aim of a study?
A general statement of what the researcher intends to investigate
To investigate the effect of alcohol on reaction times

What is a hypothesis?

A precise testable statement made @ beginning of investigation that researcher expects to happen.
Alcohol consumption will significantly affect reaction times.
Difference between the aim and the hypothesis.
Aim - General statement/ Hypothesis - Precise and testable

2 types of hypothesis


-Directional - states direction the results will go

-Non-directional - states there will be a difference but doesn't state the expected direction


-statement of no difference

-results are simply due to chance

What is the Independent Variable?
Variable that is directly manipulated by experimenter to observe effects on the DV.

What is the dependent variable?
The variable that is measured by the experimenter.

What are extraneous variables?
Anything other than the IV that can have an effect on the DV.

What are confounding variables?
Extraneous variables that do affect the DV.

3 Types of expeRIMental designs & outline:

Repeated Measures Design

- same participants in both conditions

Independent Groups Design

-Individuals randomly allocated to different conditions

Matched Pairs Design

-pp's closely matched & randomly allocated to one condition

Evaluation of Repeated Measures Design


- Individual differences are eliminated = difference between performance of conditions is due to the IV

-Fewer pp's required


- Order effects (boredom/ fatigue) - can controlled by counter-conditioning.

- Demand Characteristics because pp's in more than one condition

Evaluation of Independent Group Design


- No order effects - pp's only in one condition

- Reduced Demand Characteristics

- Same material can be used in both


- Individual differences

-More pp's required.

Evaluation of Matched Pairs Design


- No order effects

-No demand characteristics

-Reduced individual differences

- Same material can be used


-Difficult to match everything about pp's

-Very time consuming & requires more pp's

5 Methods of sampling & Outline


- Every member has an equal chance of being selected

-e.g names in a hat / computer programmes also generate random lists


- selecting every nth pp

- e.g every 5th person


- Subgroups identified

- pp's obtained from each strata in proportion to occurrence in population.

- Selection by random allocation


- most common method

-simple approach anyone available

-e.g in the street


- advertisement used

- pp's volunteer themselves

- incentive usually needed

Evaluation of Random Sampling


-Unbiased b/c pp's have equal chance


- may not be representative

-e.g. too many males

Evaluation of Systematic Sampling


- Reduced investigator bias


- Not representative = limiting generalisability

Evaluation of Stratified Sampling


- Avoids investigator bias

- Representative = can be generalised


-Very time consuming to identify subgroups & randomly select pp's.

-If all key features not identified = not representative

Evaluation of Opportunity Sampling


-easiest method - takes less time


-May be unrepresentative

-Researcher may consciously or unconsciously show bias - limiting generalisability.

Evaluation of Volunteer Sampling


- easy method - less initial work than random sampling


-Sample bias = only certain types of pp's volunteer (atypical respondents)

Aims of pilot studies

1. Check that procedures, materials & measuring scales work.

2. Allow researcher to make changes or modification.

Demand Characteristics

Cues in the experiment that make pp's aware of aims of study.

- Leads to participant reactivity which confounds the results:

- PP's try to help

-PP's try to sabotage results

- Display social desirability bias

Solved by a Single Blind Technique

Investigator effects

-Investigator has an effect on pp's performance

-researcher's physical characteristics, cues (verbal/non-verbal) and expectations can have an effect.

Can be solved by a Double Blind Design - neither pp or research know aims or use standardised instructions

What is an ethical issue
A conflict or dilemma faced by the researcher.

What is an ethical guideline
A means if resolving the conflict

What is the British Psychology Society (BPS) code of ethics?

A quasi-legal document that instructs psychologists in the UK about what behaviour is and isn't acceptable when dealing w/ pps.

6 Ethical Issues

1. Informed Consent

-must know true aims of the study.

-mustn't be coerced.

2. Deception

-mustn't be deliberately misled or researchers deliberately withhold info.

3. Protection from harm

- PPs should be in the same state after taking part as before.

- Researchers must avoid any risk greater than everyday life.

4. Confidentiality

- Personal info protected

- A legal right under the Data Protection act.

5. Privacy

- People don't expect to be observed by others in certain situations.

6. Right to withdraw

- PPs must be free to withdraw @ any time & data destroyed







How to deal with lack of informed consent

Prior General Consent

-asking people who volunteer in research general q's before research.

-Those who agree may be chosen

Presumptive Consent

- asking a group similar to the pps whether they would participate in the study.

How to deal with deception & lack of protection from harm


- After study, reveal true aims , offer opportunity to withhold data & offer appropriate support.

How to deal with confidentiality


- Research shouldn't use pp's names, numbers or false names instead.

How to deal with privacy
Allow pp to withdraw their data after study

How to deal with right to withdraw

Remind pp @ beginning, during & end of study they can withdraw.

4 General Ways to Deal With Ethical Issues

1. Ethical Guidelines - help establish whether research is acceptable.

2. Ethics Committee - must approve any study before it begins.

3. Cost Benefit Analysis - difficult to predict both costs & benefits prior to study.

4. Punishments- may be barred from practising psychology.

What is the role of peer review?

- Quality control system to make sure no incorrect or faulty data enters the public arena.

- Checks validity, originality & significance of research.

- Helps to ensure that any research paper published in a well-respected journal is high quality.

- Weeds out poorer research and allows only the best to become public.

Process of peer review:

- Number of reviewers per research

- They read the work carefully and assess all aspects of it

- Then send it back to editor w/ comments & recommendations.

- Research will be published, rejected or revised in some way.

Evaluation of Peer Review


- Establishing validity & accuracy or research

- Suggest Improvements


- Bias - Reviewer's theoretical view may differ from research

- Failure to detect fraudulent research - fabrication (made up), falsification (altered) & plagiarism (copied)

- File Drawer Phenomenon - favours positive results.

Implication of Psychological Research for the Economy

The development of treatments for mental illness

- Absence from work costs £15 bill a year

-1/3 of all absences due to mild to moderate mental health.

- Led to effective treatment for psychological disorders: SSRI's treats depression and OCD

and return back to work.

Improving Memory

- Cognitive interview technique has improved amount of correct info collected from eyewitnesses.

- Reduce expenses on wrongful arrests & to ensure criminals are caught.

Qualitative VS Quantitative Data


- Non-numerical



- Rich and Detailed

- Low in reliability

- Used for attitudes, opinions & beliefs

- Real life settings





- Precise

-High in reliability

- Used for behaviour

- Artificial setting

Primary Data VS Secondary Data

Primary Data


-Time & Effort

- Expesive


Secondary Data

- Variation in quality

-Minimal Effort

- Cheap

Measure of Central Tendency


- average

- add all, divide by number of categories.


- Mid-point of all values


- Most common value (2 modes = bi-modal)

Advantages & Disadvantages of central tendency


Ad: use of all data = most powerful

Disad: misrepresentative if there are extreme values


Ad: Not affected by extremes

Disad: Not as sensitive & may unrepresentative as doesn't include all values.


Ad: Not affected by extremes

Disad: Doesn't use all the scores & not useful when there are several modes in data set.

Measure of Dispersion


- take away lowest value from highest value.

Standard Deviation

- measure of spread of scores around the mean

- larger the SD, larger spread of score

Advantages & Disadvantages of measures of dispersion


Ad: Quick & easy to work out

-full account of extreme values

Disad: Can be distorted by extreme values

Standard Deviation

Ad: more sensitive measure than range

- Allows for interpretation of individual scores.

Disad: More complicated to calculate.

- Less meaningful if data are not normally distributed.

Normal Distribution...

- Bell curve

- Mean, median & mode @ midpoint of graph

- Graph is symmetrical

- Expressed in SDs

Skewed Distribution...

Positive Skew

- most scores fall below the mean

-data concentrated towards left

- long tail to the right

Negative Skew

- most scores fall above mean

- concentrated on the right

-long tail to the left

The sign test...

- To determine whether the difference we have found is significant.

- Investigation must be looking for difference.

- Must be a repeated measures design

- Must be nominal data.

- The S value is the lowest value of either +s or -s