Randomization may Avoid Bias

Randomization may avoid Bias
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Randomization may avoid Bias
Following the randomization of the sample population, the two resulting sample group were as shown in the image below.
1) How many older students were randomly allocated into the treatment group and into the control group?
In the generated sample random group, the even numbers (older students in the treatment group) are: 14, 6, 24, 22, 44, 32, 2, 34, 38, 10, 16, 20. There are 12 even numbers, so there are 12 older students in the treatment group. Given that the total number of older students in the sample is 50, there are 13 older students in the control group.
(2) Do you see any difference in the number of students in each group?
Yes, there is a difference in the number of students in each group. The treatment group has 12 students, and the control group has 13 students.
(3) Is this difference troubling or a potential confounder in your study?
With only a difference of one student between the treatment and control groups, the imbalance may not be significant or troubling in this case. Generally, a slight difference like this is less likely to introduce substantial bias or confounding.
(4) Can age and/or employment be a factor that could also explain a difference in final course grades between the groups in addition to the effect of different content delivery modes?
Yes, age and/or employment can still be factors that might explain a difference in final course grades between the groups in addition to the effect of different content delivery modes. Older, em...