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Variables in Statistics

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Independent and independent variables are statistics and experimental processes. An independent variable, as the word suggests, is a variable that does not depend on anything, and it is not affected by any changes that occur in other variables (Losh, 2017). Independent variables are fixed and are referred by some scholars as explanatory variables. They are the variable whose change is not influenced by other factors in the experiment. The researcher changes either the variable or it changes on its own with time. A good example is an age; it cannot be added or reduced by the researcher, and it is not affected by anything else except time, which no one has control over. The dependant variable, on the other hand, depends on other factors and, sometimes, manipulation of the independent variable (Losh, 2017). It is sometimes known as the responding variable as it values changes is influenced by changes that are made on the independent variable.

Unlike independent and dependent variables, which are the main focus of an experiment, extraneous variables are not important to the research but can still affect. These are the factors that are not studies but can highly affect the outcome of the experiment. They can be situational or participant variables, which are the individual characteristics in the area or population of the study (Rosenberg, 2017). they can also be experimenter effects or demand characteristics. Control of these variables is done through randomization, which, although it does not eliminate the extraneous variables, it ensures they are almost the same in the study population (Rosenberg, 2017). Furthermore, they can be controlled through the use of experimental designs, which ensure there an effect of the variables is insignificant.

 

 

References

Losh, S. C. (2017). Dependent and Independent Variables. The WileyBlackwell Encyclopedia of Social Theory, 1-3. Retrieved from https://onlinelibrary.wiley.com/doi/abs/10.1002/9781118430873.est0622

Rosenberg, M. (2017). Extraneous variables. Research Design: The Logic of Social Inquiry, 263.

 

 

 

 

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