Research Methods

Frage	Antworten
Research Methods	Conformity - Often referred to as majority influence Compliance - The person conforms publicly but continues privately to disagree Internalisation - A person may become a vegetarian after sharing a flat with a group of vegetarians at university Dual-Process Dependency Model - Normative social and Information social influence
Normative Social Influence - Behaviour to fit in with the group and avoid ridicule – an example of compliance. Informational Social Influence - Most likely to occur when: - Situation is ambiguous - A situation is in crisis - We believe others to be experts	Psychologists are obliged to consider the psychological well-being, health, values and dignity of their participants. If they do not do this properly, their research is described as unethical. Researchers should strive to ensure that their research is as ethical as possible. Problems arising from conflict between: What is necessary for the research The moral obligations towards participants.
Deception Right to withdraw Informed Consent Protection from harm Privacy and Confidentiality	Deception Deception should only be used if there is no alternative Deception shouldn’t be used if it is likely the participant will be unhappy when they discover the true nature of the study
Right to withdraw We must make participants aware that they are free to leave a study at any time. They can also refuse permission for their data to be used	Informed Consent Participants should be briefed with as much information as possible about a study to enable them to make an informed judgement as to whether to take part or not
Not everyone is capable of giving informed consent We need to take special care when studying vulnerable people who may not understand the implications of taking part in a study	Protection from harm Participants’ psychological and physiological safety must be ensured We cannot expose them to greater risk than their normal life experiences
Confidentiality Information about our participants is protected by the Data Protection Act They must not be identifiable in published research Participants are given numbers or referred to by a code or their initials	Debriefing We must always debrief participants after a study to allow them to ask questions and for the researcher to remind them again of their right to withdraw
Repeated Measures Design Participants take part in both conditions of the experiment	Strengths - Any differences between conditions are likely to be due to changes in the IV and not due to participant variables. - Fewer participants need to be recruited, as they are used twice.
Limitations - Order effects (e.g. practice effect, fatigue effect, recognising demand characteristics) as participants take part in all conditions.	Independent Measures Participants only take part in one condition of the experiment (2 separate groups)
Strengths - There are no order effects as participants only take part in one condition so cannot get better through practice, or under-perform due to fatigue, or change their behaviour due to demand characteristics. - It allows task variables to be controlled for example participants can be given the same word list in each condition so that this does not become a confounding variable.	Limitations - Any differences between conditions could be due to individual differences in participants, for example one group could do better on recall because they are more motivated or more intelligent.
Matched Pairs Design Participants are matched in each condition for characteristics that may have an effect on their performance. e.g. A memory test	Strengths - There are no order effects as participants only take part in one condition. - Individual differences between conditions are reduced as participants have been matched up.
Limitations - It is time consuming and expensive to match up participants	Sampling Obviously it is not usually possible to test everyone in the target population so therefore psychologists use sampling techniques to choose people who are representative (typical) of the population as a whole.
If your sample is representative then you can generalise the results of your study to the wider population.	Self-Selected Sampling Self selected sampling (or volunteer sampling) consists of participants becoming part of a study because they volunteer when asked or in response to an advert.
Random Sampling This is a sampling technique which is defined as a sample in which every member of the population has an equal chance of being chosen. This involves identifying everyone in the target population and then selecting the number of participants you need in a way that gives everyone in the population an equal chance of being picked.	Opportunity Sampling Opportunity sampling is the sampling technique most used by psychology students. It consists of taking the sample from people who are available at the time the study is carried out and fit the criteria you are looking for.
An experiment is a research method used by psychologists which involves the manipulation of variables in order to discover cause and effect. It differs from non-experimental methods in that it involves the deliberate manipulation of one variable, while trying to keep all other variables constant	Laboratory Experiments Laboratory – usually in a specially designed room with full experimenter control
Strengths - High degree of control - Replication of procedures is easy - Cause and effect: The relationship between the IV and the DV should be easy to determine as long as the experiment is well designed.	Limitations - Low ecological validity - Investigator effects - Demand characteristics
Field An experiment performed in the natural environment of those being studied.	Strengths - High ecological validity (due to natural settings, results are more likely to show true behaviour) - Reduced demand characteristics
Limitations - Less control over extraneous variables - Replication is difficult - Time consuming and expensive	Natural - Using phenomena which would occur without experimenter manipulation, e.g. closure of a factory.
Strengths - High ecological validity - Lack of direct intervention by experimenter	Limitations - Cannot demonstrate causal relationships because of lack of control over extraneous variables - Replication is difficult - Sample bias
Directional Hypothesis Also known as a one-tailed hypothesis States the expected direction of your results (It will say which group will do better)	Non-directional hypothesis Also known as a two-tailed hypothesis Predicts there will be a difference buts doesn't say which group will do better
Independent Variable What is being manipulated	Dependent Variable What is being measured
Extraneous Variables A variable which may interfere with the dependent variable	Confounding Variables A variable which has definitely interfered with the dependent variable and confounded the results
Aims What is the researcher intending to investigate	Hypothesis A prediction of what will be found Experimental - states that there will be a difference between the two sets of scores Null - states that there will not be a difference between the two sets of scores
Null Hypothesis - Often states that there is no relationship between the variables in the study - Your results will either backup your null hypothesis or it won't - If your results don't then you reject it and go with your experimental hypothesis	Experimental Hypothesis - If you reject your null hypothesis you then accept the experimental hypothesis
Mean The Average Add up all the numbers and divide by the number of numbers	Advantages - It makes use of all the numbers in the data set. Which makes it the most sensitive measure
Limitations - It is affected by extreme scores and can misrepresent the numbers as a result - It can only be used with certain types of data	Mode The most common number Calculated by putting similar scores together and counting which one occurs the most frequently
Strengths - It can be used with nominal data	Limitations - The data may have several modes
Median Central Value Calculated by arranging scores in order and finding the mid point	Strengths - It is not affected by extreme scores - It can be used with ordinal data
Limitations - Not as sensitive as the mean as not all values are reflected	Range A measure of the spread of a set of scores, shown by the difference between the highest value and the lowest
Strengths - Easy to calculate	Limitations - Affected by extreme values - Does not give info on whether scores are clustered around the mean or spread out
Standard Deviation Measure of the spread of data around the mean. Higher the value the more variation in your scores	Strengths - More precise - Sensitive measure of dispersion than range
Limitations - Unduly affected by extreme scores - More complicated to calculate	Internal reliability Measures the extent to which a test or procedure is consistent within itself
External Reliability Measures consistency from one occasion to another	Inter-rater reliability Measures the consistency between different researchers. A test should produce the same results regardless of who carries it out

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