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Common demand characteristics include: Rumors of the study – any information, true or false, circulated about the experiment outside of the experiment itself.; Setting of the laboratory – the location where the experiment is being performed, if it is significant.
By using one of these methods to account for nuisance variables, researchers can enhance the internal validity of their experiments, ensuring that the effects observed are more likely attributable to the manipulated variables rather than extraneous influences. In the first example provided above, the sex of the patient would be a nuisance variable.
An example of a descriptive device used in psychological research is the diary, which is used to record observations. There is a history of use of diaries within clinical psychology. [20] Examples of psychologists that used them include B.F. Skinner (1904–1990) and Virginia Axline (1911–1988).
The frog pond effect is the theory that individuals evaluate themselves as worse than they actually are when in a group of higher-performing individuals. [ 1 ] [ 2 ] This effect is a part of the wider social comparison theory .
By controlling for the extraneous variables, the researcher can come closer to understanding the true effect of the independent variable on the dependent variable. In this context the extraneous variables can be controlled for by using multiple regression. The regression uses as independent variables not only the one or ones whose effects on ...
For example, in a study examining the effect of post-secondary education on lifetime earnings, some extraneous variables might be gender, ethnicity, social class, genetics, intelligence, age, and so forth. A variable is extraneous only when it can be assumed (or shown) to influence the dependent variable.
A balancing loop is the cycle in which the effect of a variation in any variable propagates through the loop and returns to the variable a deviation opposite to the initial one (i.e. if a variable increases in a balancing loop the effect through the cycle will return a decrease to the same variable and vice versa).
The same is true for intervening variables (a variable in between the supposed cause (X) and the effect (Y)), and anteceding variables (a variable prior to the supposed cause (X) that is the true cause). When a third variable is involved and has not been controlled for, the relation is said to be a zero order relationship. In most practical ...