2.2 methods Flashcards
Give reasons why case studies are scientific
General qualitative data is valid because it is in depth and in detail
it is not collected in an artificial setting so validity is high and this is presented when milner met hm In his home and observe his day-to-day experiences. He then tested him in a lab setting to which HM did not notice a difference as also settings were alien to him which proves environment does not impact the validity
Give reasons why case studies are not Scientific
they are not generalisable as the data collected is only valid for their individual or group so may not be relevant for others
case studies use quantitive data which is not reliable as it cannot be tested or repeated
Case studies are subjective as large amounts of data must be summarised by generating things are categories and the research a chooses the favourite therefore compromising objectivity
Strengths of case studies
they are rich and detailed qualitive data
they have high validity and ecological validity
they avoid practical or ethical issues
They have a vast methodology like triangulation
Weaknesses of case studies
they are very subjective for example it depends on the person interpreting the data as they may become too involved which could create observer bias
they have no generalisability
they lack replication which makes it less of a science
and they are time-consuming
What is the independent variable
It is the thing you change. In an experiment the research will always alter one variable and this is the independent variable is this variable manipulates experiment standing alone not depending on anything
What is the dependent variable
The thing you measure
What is a confounding variable
also known as extraneous, These are variables that are likely to affect the result of an investigation because they have not been controlled by the researcher. To be confident the independent variable has cause the dependent variable, the researcher must control all other aspects of experiment because if they don’t they cannot be sure that they are going to find out what they aim to investigate and this is called validity for example situation variables light aspects of the environment may affect the participants performance like if it’s too hot or too cold. Participant variables rogue sample of groups of participants that may vary slightly which could affect the results for example poor eyesight
What is repeated Measures
every participant will take part in both conditions of the independent variable.
Repeated measures are good because there are no participant variables and there is no need for protesting of a pilot study but a problem with repeated measures is something called order effects
What are order effects
When someone goes through one condition and then behave differently in a second condition because they are starting to get the hypothesis and get around this problem the researcher will counterbalance
What is counterbalancing
The sample will be split into two. One does the experimental condition and then the same group will do the control condition and vice versa the ABBA design
What is independent groups design
There are different participants in each group. In lab and field experiments the researcher will manipulate the independent variable and the research I will then randomly allocate participants either to the experimental group order the control group. Participants will take part in either the control all the experimental condition not both
what is random allocation
Making sure that each participant has an equal chance of being assigned to one group or the other. When participants are assigned randomly to their group, one group may contain more alert or skilled participants than the other. We know that these participant variables might be responsible for differences between the results of the two groups. A large sample is needed to reduce this affect and if there is a variable that can directly affect results like eyesight than a protest is done to ensure that the variable is equally distributed between the two conditions
What is matched pairs design
One way to get over the difficulties of order affects is to use a matched pairs design. The study will use different participants in each group they are matched in pairs on the basis of variables which are related to the study for example age or gender or intelligence. One of each pair is a sign to the experimental condition and the control condition and the perfect match pairs design is one that uses identical twins
What is ratio level data
ratio level data is a score on a scale such as a Test score. The crucial thing about ratio level data is that there is a meaningful score of zero which means no data. For example you can score zero on a memory test if you record no objects for a temperature of 0° does it mean that there is no heat and so this idea of absolute zero gives ratio level data a starting point
What is interval level data
interval level data is also a score on a scale but the scale doesn’t have an absolute zero. This might mean you can go into negative figures on the scale. Temperature is like this and this means interval level data does not have a fixed starting point
