Answer:
1. There are multiple methods to choosing randomly from a selection. One instance could be choosing names from a hat.
2. Dividing the groups randomly allows for an equal and fair distribution of people for the control and variable groups. The 50 people receiving the drug are the variable group, while the other 50 receiving the placebo are the control group.
Step-by-step explanation:
Random selection is used in testing in order to assure the lack of bias from researchers. In real trials, random selection would likely be done through the company's own software, or an Excel spreadsheet.
Random selection is also used in order to remove lurking variables. An example of a lurking variable could be shown as follows:
A researcher is studying a connection between heart disease and cholesterol intake. Aspects unrelated to the study could still have an effect on the quality of the results, like whether people in the groups smoked or was very stressed. Random distribution assists in removing any lurking variables - and if it can't fully remove them, it will at least distribute them fairly across the control and variable groups.
