Impact of random assignment affected by the size of the study samples.

Random Assignment
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Random Assignment
Subjects are important in research and the procedure for selecting the samples is also essential in determining the overall results of the study. Random assignment is described as implementing by a chance procedures, such as tossing a coin to enable every subject to have an equal opportunity of being assigned to any available group (Marley, 2018). Compared to a random selection in which participants are randomly selected to represent the entire population, random assignment is focused on how the selected subjects are assigned to experimental groups. In the case of a psychology experiment, once the researcher has developed a hypothesis, conducted background research on the topic and selected an appropriate experimental design, the researcher then randomly selects an appropriate group of subjects who will represent the whole population. Afterward, the researcher randomly assigns the participants to certain experimental groups or control groups in which to apply the independent variable. For the results to be accurate, the random assignment should be effective enough to ensure that the groups are almost equal so that the results from the application of the independent variable can be accurately recorded. Nonetheless, the impact of random assignment can be influenced by the size of the participants in a research study. Random assignment is most dependent on sample size since the procedure is more effective with larger sample sizes (Issel, 2004).
By using random assignments, the researcher is able to equally distribute individual differences across the conditions of the experiment, and this will ensure that the groups are as equal as possible. The procedure is commonly used for the purpose of comparison and is also regarded as useful since incorporating the procedure without using random sampling decreases the risk of bias when choosing groups (Grove, Burns & Gray, 2012). Since random selection involves selecting participants using chance tactics, the probability of coming up with equivalent groups, especially in the case of two groups is higher when the sample size is higher. As stated by Cautin and Lilienfield (2015), in the case of a sample size of 20 men and 20 women, the possibility of one group having twice as many men as women is 0.026, whereas, in a sample size of 50 men and 50 women, a similar possibility would decrease to 0.0006. This would mean that in the case of two groups, the increase in sample size increases the chances of an equivalence between the groups and this would also reduce the imbalance between the groups. However, this is only possible when the sample size is even. Since the procedure involves using chance tactics to determine the placement of the participants into the various experimental groups, then an unequal sample size will result in an unequal s...