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Jordan wants to know if temperature affects student test scores. Jordan will have a sample of 10 students. The first group (5 students) is placed in a room with a temperature of 27 degrees Celsius. The second group (5 students) is placed in a room with a temperature of 15 degrees Celsius. Jordan provides food for one of the groups and not the other. Jordan has multiple variables. What can Jordan do to reduce the variables to only 1?

User Zov
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Answer:

To reduce the variables to only one and isolate the effect of temperature on student test scores, Jordan should control or eliminate other potential confounding variables. In this case, since Jordan is interested in the effect of temperature, the following steps can be taken:

Step-by-step explanation:

  1. Keep All Other Factors Constant: Ensure that all other factors except temperature are the same for both groups. This includes factors like lighting, noise level, seating arrangements, and any other factors that could potentially affect test scores.
  2. Random Assignment: Randomly assign students to the two groups to ensure that any potential confounding variables are equally distributed among the groups.
  3. Control Group: Assign students to two groups (27 degrees Celsius and 15 degrees Celsius) while keeping the group size and other conditions similar. Provide food to both groups to eliminate the confounding effect of hunger. This way, temperature is the only variable that differs between the groups.
  4. Randomization and Counterbalancing: Randomize the order in which the groups experience different temperatures to account for potential order effects. Alternatively, counterbalance by having some students in the 27-degree group start with the colder temperature, and vice versa, to control for any potential sequencing effects.
  5. Measure and Record: Measure and record the test scores of both groups under their respective temperature conditions.

By controlling other variables and ensuring that the only difference between the groups is the temperature, Jordan can isolate the effect of temperature on student test scores. This approach helps to reduce the variables to one, making it easier to draw conclusions about the impact of temperature on the outcome variable.

i hope this helps! <3

User Marco Smdm
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