Final answer:
The independent variable in the hypothesis about the pink rose bush receiving more light is the amount of light, while the dependent variable is the growth of the rose bush. When designing an experiment, scientists manipulate the independent variable and measure changes in the dependent variable to understand their causal relationship.
Step-by-step explanation:
Identifying Independent and Dependent Variables in an Experiment
In the given hypothesis, 'If I allow the pink rose bush 25% more light than the red rose bush, then the pink rose bush will grow taller,' we are investigating the effects of the amount of light on plant growth. In this scenario, the independent variable is the amount of light the rose bushes receive, as it is the factor that is being deliberately changed. Conversely, the dependent variable is the growth of the pink rose bush, which is what is being measured and expected to change in response to variations in the independent variable.
Variables play a crucial role in the scientific method and experiment design. Understanding what to control, change, and measure is key to conducting reliable experiments. Other factors to consider controlling could include soil type, water levels, and temperature to ensure they do not affect the outcome.
Variables in Different Scenarios
In another example, where bacteria growth is measured on different types of gel, gel type (A or B) serves as the independent variable, whereas the number of bacteria after 24 hours is the dependent variable. Researchers manipulate the independent variable to observe how it affects the dependent variable. This concept is pivotal to the scientific research as it determines the cause and effect relationship within an experiment.
Additionally, the presence of a control experiment, where no new factors are introduced to the subject (in this case, no additional light to a rose bush), is important to establish a baseline for comparison and increase the reliability of the experiment.