Imagine you're doing an experiment to see how the amount of water you give to plants affects their growth.
The dependent variable is like the "depends on" part of the experiment. It's the thing you're keeping an eye on to see how it changes because of what you're doing with the independent variable. In this case, the dependent variable is the plant's growth. You're watching how tall the plants get, how many leaves they have, and how healthy they seem. So, it's like you're a plant detective, checking out how the plants respond to what you're doing.
Now, on a graph, the dependent variable is usually shown on the side, like the y-axis. Think of the y-axis as the "Yes, it changed!" line on the side of the graph. Here, it's showing the measurements of the plant's growth – maybe in centimeters or inches. So, on the graph, you'd have points that show how much the plants grew when you gave them different amounts of water.
To sum it up, the dependent variable is what you're observing to see how it changes because of what you're doing in the experiment. It's like your plant detective work! And on a graph, you'd find it on the side, showing the measurements you're taking. Just like how you're watching the plants' growth change, the graph helps you see those changes more clearly.
The text provided aligns with certain aspects of both the New York State Next Generation Science Standards (NYSSLS) in Living Environment and the National Next Generation Science Standards (NGSS), particularly in the domain of scientific practices and experimental design. Here's how it aligns with these standards:
New York State Next Generation Science Standards (NYSSLS) for Living Environment:
LS1: Scientific Inquiry
Develop and use models to illustrate and explain phenomena and to make predictions.
LS4: Biological Evolution
Construct an argument supported by evidence for how increases in human population and per-capita consumption of natural resources impact Earth's systems.
National Next Generation Science Standards (NGSS):
Science and Engineering Practices:
Planning and carrying out investigations: Make observations and/or measurements to produce data to serve as the basis for evidence for an explanation of a phenomenon or test a design solution.
Crosscutting Concepts:
Cause and Effect: Cause and effect relationships are routinely identified, tested, and used to explain change.
The text focuses on explaining the concept of the dependent variable in an experiment and its representation on a graph (the y-axis). This aligns with the scientific practices of planning and carrying out investigations and making observations or measurements to produce data for evidence. It also touches on the idea of cause and effect, as it emphasizes how the dependent variable changes in response to changes in the independent variable.
Overall, this text helps students understand key concepts related to experimental design, data collection, and graph interpretation, which are important skills in science education and are reflected in the NYSSLS and NGSS standards.