Your experiment has a clear design that includes treatments, response variables, and concepts of random selection and assignment. Here’s how you could refine each of these aspects:
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Treatments:
- You correctly identified that the treatments in your experiment are the two different types of growing medium: soil and sand. Each group of sunflower seeds is exposed to one of these conditions.
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Response Variable:
- You've identified the response variable accurately as the amount of plant growth. This could be measured in several ways, such as the height of the plants after one month, the number of leaves produced, or overall health of the plants.
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Random Selection:
- Random selection applies when you choose the sunflower seeds from the packet or even from a broader source (like multiple packets) to ensure that your sample is representative. However, in your specific setup, since you have only six seeds and you’re using all of them, there’s no need for random selection here. If you were taking seeds from a larger population, that would be applicable.
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Random Assignment:
- You are correct that random assignment occurs when you assign the sunflower seeds to either the soil or sand treatment. To improve the rigor of your experiment, you could shuffle the seeds or randomly select which seeds go into which type of medium to minimize any biases based on seed characteristics.
In summary, your identification of the treatments and response variable is correct, but the concept of random selection is not entirely applicable since you used all seeds. Focus on ensuring random assignment to manage the conditions effectively.