Experimental Design
Independent variable: Mathematicians traditionally refer to horizontal axis of a graph as the x-axis or the abscissa, while scientists refer to it as the independent variable. An independent variable is one that is unaffected by changes in the dependent variable. For example when examining the influence of temperature on photosynthesis, temperature is the independent variable because it does not dependent upon photosynthetic rate. A change in the photosynthetic rate does not affect the temperature of the air! Experimenters often manipulate independent variables and look for changes in dependent variables in order to understand basic relationships.
Dependent variable: Mathematicians refer to the vertical axis of the graph as the y-axis or ordinate, while scientists refer to it as the dependent variable. The dependent variable is dependent upon changes in the independent variable. For example, photosynthesis is dependent upon temperature. A change in air temperature will result in a change in photosynthetic production.
Constants: To conduct an experiment it is necessary to keep factors other than the independent variable constant. For example, if a food scientist is studying the relationship between the concentration of preservative and the growth rate of bread mold, it is important that the temperature, humidity, light and other factors be the same for all bread used in the study. If these are not kept constant, then it is impossible to determine the effect of the variable that you are intending to test.
Controls: Experiments also require a control, or specimen that is not subjected to the procedures affecting the rest of the experiment, thus acting as the standard against which the results are compared.
Activity 5.5.1 – Interpreting graphs
Figures 5.12A-5.12H show the data from a variety of experiments and studies. For each of graph, identify (1) the independent variable, (2) the dependent variable, (3) list things that must be held constant, (4) describe an experiment that would produce such data and (5) give a simple interpretation of the data.
