Asked by k
A scientist investigated the effects of morning temperatures on flower width. Which most likely could have been a source of error in his investigation?
The distance calipers were recalibrated before each data collection session.
The control group flowers were a day older than the experimental group flowers.
The measurement units were not converted during the data analysis phase.
The flower width data were collected at about the same time every day.
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The control group flowers were a day older than the experimental group flowers.
Explanation: Age can affect flower width, so a one-day age difference is a confounding variable that could produce differences in width unrelated to morning temperature. The other choices either reduce error (recalibrating calipers, collecting at the same time each day) or describe a data-processing mistake that is less specifically tied to the temperature–width comparison.
Explanation: Age can affect flower width, so a one-day age difference is a confounding variable that could produce differences in width unrelated to morning temperature. The other choices either reduce error (recalibrating calipers, collecting at the same time each day) or describe a data-processing mistake that is less specifically tied to the temperature–width comparison.
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