Why is random assignment important

5-1 Short Paper: The Importance Of Random Assignment

Imagine that you are an online tutor for an undergraduate Research Methods course. One day, you get this email:
Dear Tutor, I am having some trouble understanding why it is so important to randomly assign participants to experimental conditions. It seems to me that if you have a large enough sample, the results would probably be valid even if you didn't bother to randomize the participants. Why is it important to go through the trouble of randomizing participants? Also, if you are going to randomly assign participants, how should you do it?

Respond to this student's email, being sure to explain the concepts at the appropriate level for an undergraduate. In your response, be sure that you explain why it is important to randomize participants. Also, explain some of the ways that a researcher can randomly assign participants. Last, be sure to explain how a researcher can make valid conclusions even in situations where randomization is not possible.

I attached an example paper below do not copy it it's just an example

The Importance of Random Assignment

PSY-510-X1150 Research Methods in Psych

Random Selection and Random Assignment; two terms that should go synonymous with research study and crucial components to all things statistics. A firm grasp on these two concepts can be the difference between observing true results and just documenting an observation without real substance. An understanding of the difference between random selection and random assignment is critical to learning the benefits they provide and it should be explained before discussing their uses and contributions to a study.

Random selection is a method for obtaining a researcher’s sample group to be used in their study. The sample group is a manageable selection of subjects or participants in a study that should represent a much larger population. Random assignment is equally important to any study and is very similar to random selection, but differs in the sense that it decides how to utilize a sample population instead of how to collect it. There are many situations, in which only a random selection or only random assignment might be utilized and some even where neither play roles (Trochim, 2006). It is often found that the best or most accurate results are found when both are employed together, which is made clear by stating the benefits of random selection and random assignment.

For any researcher it is a challenge for their study group to be as much a clone of the larger population of focus as possible. For example, a study of how many people in America that love monster trucks might not be a good representation of the general American public if only white males are questioned, which account for only about 36% of the U.S. populous according to the 2001 U.S. census (U.S Census, 2001). This is where random sampling can be utilized. The more random or haphazard the sample group is generated, the most representative of the host population it usually is. Using the same example, it would be more accurate to question people at the mall because there is a much more diverse presence consisting of multiple races, beliefs, and gender. However, there is a possibility that even this method of collection may not be as random as it appears and could be improved. If the mall selected is in a specific demographic area that a large percentage of mall-goers are of a specific gender or race etc. then the study would only show how that group feels about monster trucks. To improve this, more malls should be included, but even then care must be taken that the collectors or questioners are asking anyone who will give an answer or asking every nth person entering the mall to remove their own personal bias. It is simple enough to think of ways to gather random samples and give insight to the benefits of the method but it is not the only tool at a researcher’s disposal to represent a large population in a study.

Random assignment ensures that in a study where there is a control group and a test group that the test or control group is not limited to only one subcategory of test participants. This means that a study of The Mozart Effect or the study of Mozart’s music as described by Frances Rauscher in 1993 would not represent most people if the control or the test group ended up consisting of only people who greatly dislike classical music (Jenkins, 2001). To prevent this detriment to the study the random selection technique is applied; except now it is applied to the sample group instead of the total population. All members of the sample population will be divided into one category or another instead of just reducing the size of the study group so that results can be compared and contrasted. With understanding of how these methods can be utilized it is easy to see how they benefit, but they do not always have to work in tandem.

An example that can still be an effective study that is nearly impossible to use random selection is a study where the sample group is made up of people that choose for themselves if they will participate or not. A study of this nature may consist of a sample group of a specific age group, gender, cultural group, etc. that is interested in the results of the study; therefore skewing the results. On the other hand there can be studies that begin with a large random sample, but specific people are chosen to be a control group to root out a unique occurrence. Although the two generalizing tools are not be used at the same time they still have the same benefits by themselves as they did when being used together. The generalizing tools of random selection and random assignment both increase the accuracy of nearly any research situation or study with minimal effort, but it is important to recognize that there always exist outside influences that can offset the benefits of random selection and assignment, such as a person feeling uncharacteristic of themselves during the study. There are other methods to combat these outside influences, but random selection and random assignment are simple steps towards meaningful observations that will illuminate several very common detrimental influences.

Resources:

Jenkins, J. S. (2001). The Mozart effect. Journal of the Royal Society of Medicine, 94, 170-172. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1281386/?tool=pubmed#ref1

U.S. Census Bureau. (2001, September 10). Census 2000 Summary File 1. Retrieved from http://www.census.gov/population/cen2000/phc-t11/tab01.pdf

Trochim, W. (2006). Random Selection & Assignment. Retrieved from http://www.socialresearchmethods.net/kb/random.php