Dependent Variable
The dependent variable is the outcome measured in an experiment, the quantity expected to change in response to the independent variable.
Definition
The dependent variable is what you measure to see whether your change made a difference; it "depends" on the thing you changed. It is the measured outcome recorded in the data table and plotted on the vertical axis, and choosing it means deciding exactly how and with what instrument it will be measured. That measurement procedure defines the resolution and uncertainty of the whole experiment, so the variable should be operationally defined, measured identically across all conditions, and repeated enough times that its variability within a condition can be compared to the differences between conditions.
Example
If you change the ramp height, the distance the cart rolls is the dependent variable, measured with a meter stick after each run. In a plant investigation with light as the independent variable, the dependent variable is seedling height in centimeters from soil surface to tallest leaf tip, measured daily at the same time; after 14 days the lamp group averages $9.2\ \text{cm}$ and the shade group $5.4\ \text{cm}$. For a cart on a ramp, "speed at the bottom" is operationalized as the $0.100\ \text{m}$ spacing between two photogates divided by the transit time; with times near $0.040\ \text{s}$ and a timer resolution of $0.001\ \text{s}$, the speed uncertainty is roughly $2.5\%$.
Key Insight
The dependent variable is your result, so if you cannot measure it with a number or a clear description, pick a different one. Height, mass, leaf count, and leaf color are all possible dependent variables for the same plant experiment, and each answers a slightly different question. Its precision caps what the experiment can conclude: if two conditions differ by less than the measurement uncertainty, the honest answer is "no detectable difference," not "no difference."