A statistics professor conducted a study on the effect of playing video games on a student’s test scores. On the first day of class, she randomly divided her classes into groups. Group one played video games 2 hours a day, group two played video games 4 hours a day, and group three did not play video games at all. After three weeks the students took their first test. The professor then compared the test scores of the three groups to see if the game playing made a difference in the students’ performance on the test.
Identify at least one potential bias in the sampling technique.
The experiment was not 'double blind" because the same person who compared the test scores (the professor) was aware of the reason for the experiment.
If the groups were aware of the reason for them playing the games (possible affect on test scores) this would be another potential bias.
Since there are several classes, were the conditions randomly assigned within each class or by each class? If by each class, varying conditions between each class could be a confounding variable. Even teaching various sections of the same class can lead to different conditions.
If the test was objective and tests were machine scored, scoring would not be the need for double blind, but rather what happened in the classroom before testing would need double blind conditions.
One potential bias in the sampling technique is the lack of random assignment to the groups. The professor randomly divided her classes into groups, but it is possible that there were inherent differences between the groups that may have affected the test scores. For example, if the professor unintentionally assigned students who were more motivated or had higher academic abilities to the group that did not play video games, it could lead to biased results.
One potential bias in the sampling technique in this study could be the random assignment of students into the different groups. If the professor did not use a truly random method or if there was any systematic bias in how students were assigned to groups, it could affect the validity of the results.
To identify this potential bias, one could scrutinize the process used to divide the classes into groups. Ideally, a randomization method such as flipping a coin or using a computer-generated random number list would have been employed. If, for example, the professor assigned students based on personal preferences or any other non-random factors, it could introduce bias into the study.
To understand if there is a potential bias in the sampling technique, it would be necessary to gather information about the process used to assign students to different groups. Analyzing any patterns or deviations from random assignment could help determine if bias is present. It may also be useful to compare the characteristics of students in different groups to identify any systematic differences that could have influenced the results.