The Experiment VariablesOur experiment involves taking sheets of glass and coating them with sunscreen lotion of different SPF ratings, then placing the coated sheets of glass under bright sunlight and taking a UV reading behind the coated glass.
All of these variables are called control variables. Notice that when you're designing the procedure for your project, you must include steps for measuring the results of all of the experiments.
As you design your experiment procedure, you need to identify the independent variable, and how to measure how the changes in the independent variable affects the dependent variable. Bear in mind that there can only be one independent variable. All other variables must remain constant. This is the ensure that any changes in the dependent variable can be properly attributed to changes in the independent variable. In our example, we need to ascertain how changes in SPF ratings affect the level of protection. If you don't keep all other factors constant during the experiment, other than the SPF level (for example, if one control experiment was done under bright sunlight whilst another is done late in the evening during sunset), you won't be in the position to say that the results which you observed were caused by the changes in SPF levels. Your procedure should also specify how many trials are to be performed. At a minimum, you should repeat your experiment three times, although there's nothing to prevent you from repeating more. For experiments that involve surveys, there's no sense in asking the same person the same question more than once - however, for this type of experiment, you should ensure that you survey a large number of participants for more reliable results.
Watch out!All scientific theory must be substantiated by reproducible test results. These tests must be reproducible by other people. That is why it is so important for you to keep good, systematic records of your experiment!
As you perform your experiment, you need to watch out for the following types of errors or mistakes:
1. Errors in the measuring instruments that you are using.
Because this type of error will always produce a measurement that is higher or lower than the "true" value, it is called random error.
2. Systematic errors (also known as non-random errors), which are due to factors which bias the results of your experiment in one direction.