At some point in your student career, you may have spent hours “learning” something, only to realize you were memorizing facts and not truly thinking about what you were studying. When you take time to reflect on what you are learning, do you always agree with the information? Has taking the time to truly understand a topic ever changed your perspective?
Critical thinking, or systematically evaluating information before accepting or rejecting it, enables individuals to move beyond memorization of facts to truly learning about the world. The basis of scientific study is critical thought. Although fields such as biology are often used synonymously with the term, science actually refers to studying anything through objective, critical thinking about observations of the world.
Science strives to provide objective, testable answers to questions naturally arising from observation. It avoids subjective questions and answers better addressed by religion and society. Although scientific theories often spark controversy in human societies, a scientific hypothesis is meant solely to provide a testable, falsifiable explanation for observed natural phenomena. As you study biology, carefully consider each hypothesis or theory based on the observations and other available data before drawing conclusions.
Traditionally, the scientific method has been taught as a linear progression from observation to hypothesis to experimentation to conclusion. In reality, the scientific process follows a general framework in which observation is critical throughout. Focusing on the progression of logical thought involved in both science and everyday life is more important than following steps in a “scientific method.”
Although observation and investigation are extremely valuable, science progresses only with innovation and creativity. If every scientist only proposed existing ideas, how could we improve understanding of the world? A hypothesis, or logical explanation for a set of observations, provides a framework for continued investigation of a situation.
Scientific processes require a hypothesis be derived by objective analysis of existing data, but moving from facts to a logical explanation of the facts often requires creativity. A hypothesis must be falsifiable, able to be proven incorrect by experimentation or continued observation. The nature of the scientific process requires that no scientific hypothesis can ever be proven true because it is impossible to know every piece of relevant data. Scientific knowledge is growing exponentially, and future observations or experiments could change what we understand about any topic. An objective explanation of existing facts could be proven false at any time by discovery of new facts contradicting the hypothesis.
The classical, step-wise scientific method involves inductive reasoning to develop a hypothesis deriving most logically from available data. Hypotheses may be generalized, but are usually specific to what can be observed and analyzed in a reasonable time frame. Deductive reasoning generates a specific set of testable predictions. Finally, testing specific predictions may disprove, support, or modify the hypothesis for additional testing.
Some scientific methodologies focus on a discovery process, using observations and extensive data analysis to develop new or global ideas. Hypotheses derived from this kind of scientific method are frequently innovative, using inductive reasoning to draw conclusions that change the way scientists view a topic. The goal of discovery-based science is to focus on the observations and data alone, avoiding the potential bias of seeking data to match an existing hypothesis.
In scientific research, complex or multifaceted hypotheses may encompass several supported, specific hypotheses or may be derived from the synthesis of a large volume of existing data. Because of their complex nature, years of testing may be required to collect new data to support or disprove this kind of hypothesis. With enough supporting evidence, a multifaceted hypothesis is designated a theory.
Although one “scientific method” does not exist, scientific investigation follows a basic framework to guide critical thinking about an observation or set of observations. Depending on the nature of the observation or question, scientists follow a progression of steps leading to objective hypotheses supported by data. Scientific methodologies are applicable in more than biology; they are valuable in every aspect of life.
This activity explores the framework for scientific processes, from observations and questions to a logical conclusion.
Testing a Hypothesis
Disproving or providing support for any new hypothesis requires experimentation, observational study, and/or analysis of existing data. Experiments are scientific studies that assess a hypothesis by testing its predictions. In an experiment, scientists manipulate one factor, the independent variable, in order to discern its effect on another factor, the dependent variable. Conclusions about cause and effect can be drawn only when all other variables are controlled (kept constant). For comparison, a control group is tested in tandem with the experimental group. All factors except the independent variable are kept the same in both control and experimental groups in order to attribute differences in the dependent variable to changes in the independent variable.
When a problem cannot be analyzed by manipulation of the variables involved, comparative studies, extensive analysis of existing data, and systematic observation of new situations or environments may be used to evaluate a hypothesis. Many hypotheses cannot be tested directly and require extensive use of observational study and data analysis. Systematic, organized data collection and analysis disproves or provides support for hypotheses, but effort is required to avoid bias or inappropriate conclusions. Sometimes, correlation is mistaken for causation in non-experimental studies. When two events occur together frequently (correlation), drawing conclusions about the relationship between them (causation) may be premature, or even incorrect.
Sometimes, a hypothesis may describe a causal relationship between variables that cannot be investigated further through collection of correlation data, particularly in human studies. Scientists will sometimes use a model system to allow experimental analysis of the hypothesis. A model system is a living organism whose biology is analogous to human biology, at least in regards to the variables under investigation. Unlike human subjects, model organisms can be manipulated to control external variables in an experiment, allowing cause-and-effect relationships to be examined. Experiments in model systems provide additional support for causative relationships between two variables. For example, a high correlation between smoking and lung cancer exists in humans. Scientists cannot set up control and experimental groups of humans and ask them to smoke, or not smoke, for years in a controlled laboratory environment. To evaluate possible causative effects of smoking on lung cancer, studies are performed using rats as a model system. Although data collected in model systems may be affected by differences between humans and the model system being used, combining experimental data in one or more model systems with observational data in humans can provide stronger support for a hypothesis than either data set alone.
New data is analyzed in an objective manner to avoid bias. A hypothesis that is not supported is either discarded or modified in response to the complete body of data. A supported hypothesis is subject to additional testing until the body of supporting evidence is so extensive scientists no longer actively test it. Although many well-supported hypotheses have become integrated parts of textbook material, listed as though they are “facts,” science can never prove a hypothesis. As you read a textbook, try to distinguish between observations and data, and the well-supported explanations derived from them. Consider whether you agree with the logic and support for each explanation separately. If you feel more evidence is necessary, do some additional research and see if you agree or disagree after you have gathered additional data.
A hypothesis that is broad enough to affect perspective on many scientific observations and phenomena becomes a theory when the supporting evidence is strong enough that continuing to test the main premise is considered a waste of resources. Many important theories begin with one or more observations so groundbreaking that the observations require a universal descriptor. The law of gravity is a classic example. In science, the term law refers to a very well-tested observation (or set of related observations) significant enough to affect a wide range of scientific investigations. Scientific laws only describe a phenomenon; they do not attempt to explain how the effect occurs. In this example, the law of gravity is the equation describing the response of objects attracted to one another, but does not explain why the objects are attracted. As physicists learned more, they were able to test the explanations, until hypotheses explaining the law of gravity were supported by enough evidence to become gravitational theory. Despite widespread evidence to support gravitational theory, science dictates that if an object were to behave in a way counter to the current understanding of gravity, scientists would discard gravitational theory and seek to find a new, testable hypothesis to explain the existing observations, including all new data.
Many factors play a role in good experimental design and evaluation of results. This acitivty demonstrates the importance of proper set-up, quantitative measurement, and avoiding bias in drawing conclusions about a hypothesis.
Scientific Method Terms
This activity tests your ability to match terms used in the scientific method with their definitions.