Psychological Investigations.


Mind map on psychology methods
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Copied by xCocoPopsx13x almost 10 years ago

Resource summary

Psychological Investigations.
  1. Self reports
    1. Questionnaires
      1. Questionnaires are an easy method to gain data,as the P's record their own answers. They also use a range of open and closed Q's to gather the data.
        1. Open Q's: Open Q's allow the P's to record their own answers and to expand upon why they think something & give their opinion.It can also be used as a way of expanding upon an answer given in a closed Q. Open Q's tend to produce qualitative data, which means when analysing, you look for trends in the answers.
          1. Closed Q's provide limited answer choices and provide quantitative data and the answers are easy to analyse.
        2. Interviews
          1. Two types of interviews: Structured and unstructured:
            1. Structured interviews use pre-determined Q's that are restricted in terms of answers.
              1. Unstructured interviews have no pre-determined Q's.
            2. Likert scales
              1. Likert scales can be used to assess the strength of a person's opinion. They are also an example of a closed question and provide quantitative data.
                1. However, when using a Likert scale, P's may avoid the extreme ends of the scale and only use the middle value, thus not displaying their true opinion.
            3. Experiments
              1. The IV and DV:
                1. The IV is the variable you are deliberately changing/controlling and the DV is the outcome of this change. From this we can establish a cause and effect relationship.
                2. Controls
                  1. The experimenter controls the IV to see if changes in the IV lead to changes in the DV.
                  2. Hypotheses:
                    1. Experiments use a hypothesis to "predict" the outcome of the experiment. A hypothesis is a testible statement and states that there will be a difference found.
                      1. The opposite of a hypothesis is the null hypothesis, which a 'statement of nothingness': i.e "There will be no difference"
                        1. Experiments use an experimental hypothesis, while every other study uses an 'alternate hypothesis' as they are not experiments
                      2. Three types of experiments: A lab experiment manipulates the IV and uses controls and takes place in a lab environment. A field experiment still manipulates the IV, but takes place in a natural setting. A natural experiment has a natually occuring IV that isn't manipulated by the experimenter.
                        1. Strengths: From the data gathered we can assume a cause and effect relationship and by manipulating the IV we can observe the effect it has on the DV.
                          1. Weaknesses: P's are in an artifical situation which may lack realism and P's may respond to the experimenter cues. This may mean the results can't be generalised.
                          2. Correlations
                            1. A correlation is a way of measuring the relationship between two variables. A positive correlation is when the two variables increase together. A negative correlation is when one variable increases while the other decreases. A zero correlation is when there is no relationship between the two variables.
                              1. Strengths of correlations: Correlations can be used when it would be unethical to conduct an experiment. If the correlation is significant, then this justifies further investigation. If the correlation isn't significant, then you can rule out a casual relationship.
                                1. Weaknesses of correlations: Data can be mis-interpreted and assume a cause and effect relationship, where it isn't possible to do so; As you can only find a link between the two variables. There may be other unknown variables that explain why the co-variables being studied are linked. Extraneous variables can lead to a false conclusion.
                                2. A scattergraph is a graph that shows the relationship between two sets of data (co-variables) by plotting dots to represent each set of scores. For each individual, we obtain a score for each co-variable.
                                  1. The extent of a correlation is described used a correlation co-efficient. This is a number between +1 and -1. +1 is a perfect positive correlation and -1 is a perfect negative correlation.
                                    1. By using a correlation, we can assume a link between the two variables, but we can't assume a cause and effect relationship.
                                  2. Designs: For experiments, designs are used to organise the P's in the study. Typically, there are three main ways:
                                    1. Independent measures: This is when two different groups are used in two different conditions.
                                      1. Repeated measures: This is when the same group of P's are used in two or more different conditions.
                                        1. Matched pairs: As independent measures but the P's have been matched according to the variable that is being investigated.
                                        2. Observations
                                          1. Time sampling: The observer keeps a count of each time a particular event is displayed.
                                            1. Event sampling: The observer decides on a time interval, such as once a minute. At the end of the time interval, the observer notes any particular behaviours that are being displayed by the target individuals.
                                              1. Unstructured observation: The researcher records all relevant behavior but has no system. The behaviour to be studied is largely unpredictable. One problem with unstructured observations is that the behaviours recorded will oten be those which are most visible to the observer and may not be the most important.
                                                1. Controlled and Naturalistic: A controlled observation has some variables controlled by the researcher such as the environment and the specific behaviour being displayed,e.g a task. A naturalistic observation has no variables controlled and is studied in a natural environment.
                                                  1. Structured observations: The observer breaks up the behaviours into categories and then uses the checklist to know what catergories of behaviour to observe.
                                                    1. Participant and non-participant: In a participant observation, the observer is merely watching the P's and acts as a non-participant. In a participant observation, the observer becomes part of the group that is being observed and acts as a participant and observes from within the group
                                                      1. Strengths of observations: We can observe naturalistic behaviour i.e "normal" behaviour. This is because the behaviour has eco-logical validity. We can also gather data firsthand and the observations can form the basis of future investigations. It can also be used to check what people say against what they do. It is also quick, easy and cheap to do.
                                                        1. Weaknesses of observations: There may be observer bias, i.e the observer may be subjective with what they see- "only seeing what they want to see" i.e based on their own interpretation of the behaviour and this can affect the validity. If the categories are unclear, then we may get mis-recorded data and also, ethical concerns- is it okay to observe someone without their consent?
                                                        2. Reliability and Validity
                                                          1. Validity: This is to the extent to which the research has measured what it intends to measure.
                                                            1. This is when two different measures are used to measure the same thing. If the same scores and results are obtained, then concurrent validity is present.
                                                              1. Eco-logical validiy: Does the research reflect real life behaviour, and real life condititons?
                                                              2. Reliability: Reliability is whether the study and the results are consistent, i.e If the same or very similiar pattern of results are gathered, then the study and the results are reliable.This is called test-retest.
                                                                1. Reliability can be improved by having two researchers gather the same data and results when doing the same study. To gain high inter-rater reliability, then 80% of the total data has to be agreed that it is the same.
                                                              3. Case studies
                                                                1. A case study is a research investigation that involves the detailed study of an individual, institution or event. It uses information from a range of sources, such as interviews and observations, to obtain data. These findings are often selected and organised, for instance to represent the individual's thoughts and emotions.
                                                                  1. Strength of case studies: You can gather rich and in-depth information and it allows you to see a change in behavior over time.
                                                                    1. Weaknesses of case studies: There might be attrition in the sample and the experimenter may lose objectivity in the process. Also the results gained can't be generalised to anyone else, as the findings are unique to the person(s) being studied.
                                                                  2. Sampling: When studying any behaviour, researchers can't test everyone, so they select a sample from the target population; i.e the people they are interested in.
                                                                    1. Opportunity sampling: This is the easiest method, as you basically use people who are readily available, i.e the first people you find; however it is a biased option, because the sample is drawn from a small part of the target sample.
                                                                      1. Self selected sample: This is where the P's volunteer them selves, usually be responding to an advert. By using this sample, there is access to a variety of P's, but the sample is biased because the P's are more likely to be motivated to participate.
                                                                        1. Random sampling: This is where the P's are selected randomly-i.e with no bias. E.g Names of the target population into a hat and draw out the required number. This sample is unbiased and all P's have an equal chance of participating. However, may end up with a biased sample, as not all P's identified will participate. It is also almost impossible to carry out a random sample unless the sample is very small.
                                                                          1. Systematic sampling: This is when you select every N'th person from a list.
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