Variables:

A variable is what is measured or manipulated in an experiment. Variables provide the means by which scientists structure their observations. Identifying the variables in an experiment provides a solid understanding of the experiment and what the key findings in the experiment are going to be.

To identify the variables, read the lab procedure described in the lab manual. Determine what you will be measuring and what you will be manipulating for each measurement. The value(s) you are manipulating is called the independent variable (see definition below) and the value(s) you are observing/recording is called the dependent variable (see definition below). Write down the dependent and independent variables.In more advanced labs, you may have multiple variables (see definition below), more than one independent and dependent variable

Independent and Dependent Variables:
An independent variable is the variable you have control over, what you can choose and manipulate. It is usually what you think will affect the dependent variable. In some cases, you may not be able to manipulate the independent variable. It may be something that is already there and is fixed, something you would like to evaluate with respect to how it affects something else, the dependent variable like color, kind, time.

A dependent variable is what you measure in the experiment and what is affected during the experiment. The dependent variable responds to the independent variable. It is called dependent because it "depends" on the independent variable. In a scientific experiment, you cannot have a dependent variable without an independent variable.

Example: You are interested in how stress affects heart rate in humans. Your independent variable would be the stress and the dependent variable would be the heart rate. You can directly manipulate stress levels in your human subjects and measure how those stress levels change heart rate.

Multiple Variables:
It is possible to have experiments in which you have multiple variables. There may be more than one dependent variable and/or independent variable. This is especially true if you are conducting an experiment with multiple stages or sets of procedures. In these experiments, there may be more than one set of measurements with different variables.

Example: You are interested in finding out which color, type, and smell of flowers are preferred by butterflies for pollination. You randomly choose an area you know to be inhabited by butterflies and note all the species of flowers in that area. You want to measure pollination of flowers by butterflies, so your dependent variable is pollination by butterflies. The independent variables are flower color, type, and smell. You will need to specify relationships for each of these independent variables with the dependent variable.