Experiment

An experiment is a scenario set up to gather specific information. The collected information is used to prove a theory or answer a question. Good experiments are set up in controlled circumstances to make sure the data collected is reliable. Experiments in which the researcher has a personal stake in the experiment should be set up to remove all bias from the results. Scientists, executives, doctors, students, and researchers of all kinds conduct experiments.

Overview

All experiments start with a question. Someone wants to know something, and an experiment is a way of gathering information. Depending on the researcher, an experiment's purpose may be as simple as discovering the most popular subject in a classroom, or as complicated as using the Large Hadron Collider, the largest machine in the world, to study particles so small that scientists need special equipment to see them. Whatever the purpose or methods involved, all good experiments have something in common: they follow the scientific method.

The first step in the scientific method is to ask a question. Next, the researcher does background research and develops a hypothesis. A hypothesis is a theory or proposal about the subject. As an example, a researcher develops the hypothesis, "The people who take this new medication will feel less pain than those who take nothing."

After forming a hypothesis, the researcher tests it through experimentation. An experiment is composed of several parts, including variables, constants, and trials. A variable is any part of the experiment that changes. The two types of variables are independent and dependent. Independent variables are those the researcher directly influences. Dependent variables change based on the independent variable. Additionally, an experiment should include a set of data where the independent variable is set in the way it naturally occurs. This is called the constant or control. The results of the experiment are compared against the control.

In the example experiment, the researcher takes twenty randomly selected people who are experiencing pain and conducts a trial. In this trial, the researcher prepares one dose of the new medication for each person, makes sure all subjects take it properly, and asks each participant to describe his or her experience afterwards. The researcher then takes note of how many people have stated their pain was reduced.

In this experiment, the drug that the researcher gives the participants is the independent variable, and their reaction is the dependent variable. This may seem like a simple and effective test, but it allows for a great deal of bias. Additionally, the experiment is lacking any kind of control against which to compare the results, and repeated trials to account for abnormalities.

The researcher can improve this experiment in several ways. Firstly, the researcher should allow for a control group. This can be done by splitting the participants into two equally sized groups: one that receives the pain medication and one that does not. The researcher then compares the results of the two groups. However, this does not account for biased or deceitful participants. Someone who is given a pill that they believe should have some kind of effect is more likely to report positive results than someone who is given nothing, whether the pill actually functioned as intended. To remedy this, the researcher should use a placebo. A placebo is a fake treatment, identical in appearance to the real treatment, given as a control. If none of the participants know if they have been given a placebo or a real medication, this is called a blind trial. If the group given real medication consistently reports more of a reduction in pain than those given the placebo, the treatment is most likely effective.

While this experiment is more effective than the original experiment, it fails to account for the experimenter’s bias. Studies show that researchers have a tendency to see whatever results they expect to see in an experiment. Additionally, studies have shown that when a researcher collecting information expects a certain result, the researcher subconsciously communicates how he or she expects the participant to act. Participants will change how they report their symptoms based on the researcher's unstated expectations. This is called the Rosenthal effect. Before it was discovered, many ineffective operations were carried out because medical professionals believed they helped patients.

Double-blind studies eliminate researcher bias. In a double-blind study, the researcher trusts someone else to prepare the placebo and the medication for the experiment. The pills are labeled differently, such as Group A and Group B, but otherwise appear the same. The researcher is not informed which group contains real medicine, and thus cannot influence the results of the experiment. The medication and placebos are then distributed in the same way as a single-blind experiment. The researcher is only informed which group contains real medicine after the results are completely processed. Double-blind studies are considered significantly more trustworthy than single-blind or non-blind studies.

Once the experiment has been finished, the researcher analyzes its results and draws conclusions. If those results match the researcher's original hypothesis, the researcher can declare that it was a success. If not, he or she can adjust various parts of the hypothesis or experiment and try again. A researcher may also choose to publish the results and allow the experiment to become the basis for future research.

Bibliography

"Experimental Design." Texas A&M University, 21 Apr. 2024, guides.library.tamucc.edu/c.php?g=889148&p=6391894. Accessed 15 Nov. 2024.

"Steps of the Scientific Method." Sciencebuddies.org,https://www.sciencebuddies.org/science-fair-projects/science-fair/steps-of-the-scientific-method. Accessed 15 Nov. 2024.

"The Large Hadron Collider.” CERN.ch. CERN. Web. 18 Dec. 2014. <http://home.web.cern.ch/topics/large-hadron-collider>. Accessed 15 Nov. 2024.