Research Methods Flashcards
Study revesion (56 cards)
Communality
Science and its methods are nobody’s property, but held in common by all humanity – methods available to everybody -
Universalism
scientific validity doesn’t depend on the status or identity of the researchers – science is its own thing about trying to find out about the world
Organized scepticism
scientific claims must be exposed to critical scrutin
Merton’s norms for science, simplified – scientific truth is provisional truth
ethical obligation
usually people, and we have a duty not to waste their time
Results of psychological research are often applied to how people are treated, so we’d better get it right
The Stroop Effect
reading has become so automatic that it’s hard to inhibit it
So when the colour of the print conflicts with the colour named, reaction time is slower
Dependant variable
measure of behavior we’re interested in e.g how many colours in Stroop effect, goes on y axis of a graph of our results (need to be reliable and valid)
Independant Variable
Manipulated by the exprimentor to see if it effects the DV e.g whether colour matches name on stroop effect, goes on x axis
Operational definition
Description of operations carried out by researcher to measure DV or to manipulate IV. Helps others to replicate study, and helps us to remain objective and avoid biasing our results.
Reliability
Whether we get the same results if we measure the same variable again under the same conditions.
Validity
Whether our variable really measures what we meant it to.
Population
All the events, scores etc. we are interested in. * e.g., heights of the entire PSYCH 109 class
Sample
Representative subgroup drawn from population, preferably randomly. Used to draw conclusions about whole population. g., heights of a randomly selected 10 people in the class
Sampling error
Random samples drawn from the same population will give different results. Chance variation. Unavoidable, but minimised by using large samples.
due to natural variability and can be reduced by increasing the sample size
Sampling bias
When a sample does not truly represent its parent population, usually because it was not drawn randomly. E.g., a minority ethnic group may be underrepresented. Avoidable by random sampling.
Sample misrepresents population in a systematic way
* Serious sampling bias invalidates the research
due to systematic errors in the sampling errors in the sampling process and can invalidate research findings if not properly adressed.
Observational designs:
Look for correlation between two DVs (strictly, there is no IV. Some sources, like your lab manual, use IV slightly differently, to mean the variable that may cause changes in the DV. I prefer the stricter definition that it is the variable the experimenter manipulates). Note that correlation doesn’t always imply causation, so less powerful than experimental designs, but sometimes the only choice for ethical or practical reasons.
Measure two DVs and look for a relationship between them
Sometimes called a correlational design, because a relationship between variables is a correlation
There is no IV, because nothing is manipulated
e.g., is self-esteem related to intelligence?
Experimental designs
Manipulate IV and observe (look for) effect on DV. Can imply causation, if effect is replicable. More powerful, but not always possible
is self-esteem related to results of a fake IQ test? (turned it into a IV - manipulated it
* e.g., Flourens and experimental ablation – gave dog brain damage – turned the brain damage into a independent variable not dependent and seeing what it now couldn’t do.
Experimental designs are more powerful (give us the power to do the thing) than observational, so we should use them when it’s ethical and practical to do so
When you’re evaluating research that you read about, always consider this issue – has causation really been proved?
Confounding variable
A variable other than our IV which might have been responsible for any change in the DV that we observed. An alternative explanation for our results. Invalidates our experiment. Also just called confound.
Controlling for potential confounding variables:
Hold them constant (esp. with external confounds, such as time of day, or stimulus lists in a memory task). Randomize them (esp. with subject confounds, such as individual differences in ability on a task).
Within-subject design
Each subject is exposed to all levels of IV (all conditions). Comparison is between each subject’s performance in several conditions. Internal (subject) confounds controlled, but could be external (environmental) confounds.
Between-subjects design
Each subject only encounters one level of IV (one condition). Comparison is between average performance of groups of different subjects in each condition. External variables can be controlled, but could be subject confounds.
Matched-pairs design:
Each subject is only in one experimental condition, but his/her behaviour is compared with a matched partner (according to subject confounds that might be important, like pre-existing ability at the task) in the other experimental condition. Controls both external and internal confounds. Good idea but not widely used.
Experimental group:
Group that receives the intervention (e.g., a new drug)
Control group
Group that doesn’t receive the intervention, but is otherwise treated identically to experimental group. Assess effect of intervention by comparing improvement of control with experimental group.
Placebo
A sham drug (e.g., a sugar pill which looks like the real pill). Given to control group in drug evaluations.
