Controlling for External Variables in Science


Controlling for External Variables in Science

Science is an empirical, experimental, quantitative approach to science that modifies and identifies existing knowledge in the physical, chemical, and biological sciences. The methods of scientific research are different from one discipline to another and greatly depend on the field of study. For example, in physics, experimentation is the major method of scientific research used to test and modify the existing physical laws. In chemistry, systematic methods are adopted to study the properties of matter and its interactions. And in biology, different approaches to biology are employed to identify and describe living organisms.

The most familiar example of a scientific method is the experiment, which is used to test and prove the existence and properties of a natural entity. An example of a hypothesis in science is the observation of nature, with the hypothesis that there is such a thing as a cat in this world. With the help of scientific methods, we can conclude that there is such a thing as a cat, and so on. It could be proved or denied by various scientific methods. It would then be used as the main line of evidence to explain and support any other phenomena that are similar to it.

One example of an experiment is the controlled flight trial conducted during the AIDS epidemic. A thousand and five aircraft were fitted with early warning sirens, which started emitting orange lights when they were hit by someone in the infected area. The aim of this experiment was to test and see if early treatment would reduce the fatalities caused by the disease. The results showed that although early treatment reduced the mortality rate, it was not as efficient as the prevention method using the scientific method.

It is important to know how to apply scientific methods, since this is how we arrive at conclusions and arrive at our predictions and projections regarding the future course of the natural phenomenon under study. For instance, in biology, it is important to determine whether the genetic structure of species is consistent or if species are truly independent. This can only be determined using a systematic approach and observation of patterns and relationships among the independent variables. In this case, it is necessary to carry out a number of experiments on a variety of species, and then come up with a hypothesis concerning the consistent or independent variable. Once this hypothesis is tested, a causal relationship between the independent variable and the dependent variable can then be deduced.

It is also important to keep in mind that the scientific method cannot make predictions, and cannot provide absolute certainty in terms of the results. Scientific knowledge is limited to the existing data. There are still a lot of theories that are being worked on, but science has developed the means of arriving at a concrete set of predictions. At the same time, science technology has been successful in producing machines and equipment that can solve problems more easily and efficiently than human scientists. Science technology has also made possible the construction of artificially intelligent computers, which are now helping to solve human problems on a daily basis. Hence, the progress made in science and technology has greatly contributed to humanity’s well-being.

A problem that often occurs in science experiments is the use of a control group or an extraneous variable in the model. Although the model may not be well-fitted to take into account all the independent variables, it remains important to include control factors in the model. For instance, in a study that intends to study the effect of smoking on lung cancer, it is important to control for the effect of smoking on the independent variables of age (the age at starting smoking) and gender (the gender of the smoker). Age and gender are significant external factors affecting the risk of developing lung cancer. Likewise, it is important to include in the model the effect of a given level of physical exertion on the incidence of a particular disease, because physical exertion is another independent variable that can potentially affect the risk of developing a particular disease.

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