The scientific method is the "process of science" and the experimental process is the basis for the scientific method. It is the experimental process that makes the hypothesis to the test. In this step, the empirical data for interpretation shall be gathered. The experimental process is the difference between true science and "junk science".
Let discuss us to clarify some terms.
First hypothesis. A hypothesis is an idea that proved to be not right or wrong; It is someone's opinion. It must be tested vigorously for a hypothesis as to be considered. While the testing process, many data must be collected and analyzed later. If the data supports the hypothesis. It is presented to the scientific community for further review. However, if the data not the hypothesis supports there is should be discarded as junk-e-science treated.
As the next real science. True science is empirical data supported by the scientific process. If a statement is not supported by data, it is a hypothesis or "junk science". Many so-called scientists today are not scientist but a philosopher. You do not have empirical data to support their hypotheses, but write about their ideas and thoughts. Avoid those who propose scientific information without empirical evidence.
Finally the experimental process. The experimental process is an extension of the scientific method, in which the hypothesis to the test is made. It is here that you capture organizes data, analyzed and interpreted. So, you must understand how these functions process.
The experimental process
State the problem Testing begins with writing clearly the hypothesis. The problem and the possible results should contain.
Know the variables - once you know where you go, you must decide what you are looking for during the test. It is important to limit the test to an independent variables to get the best data. If you are more than a variable that try need creating separate tests for each variable.
How to determine the controls - Controls are changed the elements of the experiment, that throughout the process. You have control of the factors to the not tested and prevent that these factors disturb your independent variables.
Design an experiment - now that you have the variable and controls, it is time to design an experiment. Designing the experiment is probably the most difficult step in this process. You must determine your materials, procedures, those who follow, and how you collect your data.
Collect Data - there are two types of data you need to collect: qualitative and quantitative. Qualitative data are non-numeric information in the form of written descriptions of direct observations. Quantitative data are collected and recorded in the form of tables, charts, and equations numeric information by measurements.
Although both types of data are important, quantitative is more efficient, safer and less likely as qualitative data are misunderstood. But qualitative data is far more descriptive and more difficult to generalize. So, both types of data are required.
Repeat the attempt - continue to the test repeat until you have collected enough data either support or refute the hypothesis.
After the data has analyzed, the scientist must interpret the results and write a degree. The scientist conclusion should explain what the problem was whether it was solved and how the solution supports the data.
Finally, the scientists of the conclusion and the supporting data in a scientific journal for all scientists read will publish. The scientists will work being reviewed, tested and questioned, whether the results are true and perhaps the new findings, a new theory to bear.
