Sampling, Variables, and Study Design
The subgroup drawn from a specified population makes up the sample (Welkowitz, Cohen, & Lea, 2012). In this case, the sample is three-hundred university freshman of the local university and the population would be representative of all of the university undergraduates at that local university. Alternatively, this could be a poor representation of all U.S. undergraduates. The factors to consider is whether or not the results would be the same if they applied to a different population. The sample can only apply to the population that the sample was drawn in the case of generalizing (Welkowitz et al., 2012).
The survey in question is categorized as a ordinal scale due to its use of numbers scored on a 1 to 5 scale (Welkowitz et al., 2012). This differs from a nominal scale that is measured by assigning names or categories (Monash University, n.d.). In addition, this study is correlational because it is directly measured without manipulating any of the data. Likewise, the researcher does not infer causation.
If self-esteem was measured by telling some of the students that they were well liked by their classmates and others were told they were not well liked before they took the test, we can infer that the independent variable is the students self-esteem. This is a variable that could be manipulated by telling the students whether they are liked or not (“Independent Variable,” n.d.). The dependent variable is their I.Q. It is not only dependent on self-esteem, but it is what we are measuring and is affected during the experiment (“Dependent Variable,” n.d.).
References
- Dependent Variable. (n.d.). Dependent Variable. North Carolina State University. Retrieved April 20, 2014, from http://www.ncsu.edu/labwrite/po/dependentvar.htm
- Independent Variable. (n.d.). Independent Variable. North Carolina State University. Retrieved April 20, 2014, from http://www.ncsu.edu/labwrite/po/independentvar.htm
- Monash University. (n.d.). Monash University. Retrieved April 21, 2014, from http://www.csse.monash.edu.au
- Welkowitz, J., Cohen, B. H., & Lea, R. B. (2012). Introductory Statistics for the Behavioral Sciences (7 ed.). John Wiley & Sons, Inc. ↩1 ↩2 ↩3