Science is simply defined as the study of the natural world. Although there are many disciplines within science, all scientific understanding is reached using a systematic gathering of observations and evidence. The investigations that scientists use to gather this information vary and can be descriptive, comparative, or experimental in nature. Once scientists conduct investigations using a range of methods and technology, they can begin to form explanations about natural phenomena. Over time, these explanations are collected in the general body of scientific knowledge and are used to form laws and theories.
If science is defined as the study of the natural world, then scientific inquiry is defined as the myriad ways in which scientists conduct their studies and form explanations. There is no one set path that all scientists must follow in order to conduct scientific inquiry, but observations, hypotheses, variables, controls, drawing conclusions, using sources, and communicating findings all play major roles in the process.
Observations, or the receipt of knowledge of the natural world using senses or technology, are considered the core element of scientific inquiry. Observations can be quantitative or qualitative in nature. Quantitative observations are ones which can be measured, such as number, length, mass, or volume. Conversely, qualitative observations cannot be measured and are general qualities, such as color, shape, or texture.
Scientists observe the natural world in order to collect data of natural phenomena, or any state or process that occurs in nature. These observations are used to propose scientific explanations that describe how and why these phenomena occur. A proposed explanation of natural phenomena is also known as a hypothesis. Once a testable hypothesis is formed, then a scientific investigation can begin.
A hypothesis is more than an educated guess. Instead, a hypothesis is a testable proposition that scientists can use as the basis for an investigation. If it is not capable of being tested scientifically, it is not a hypothesis.
Every experiment includes variables, which are the factors that may impact the outcome of the experiment. Independent variables are controlled by the experimenter. They are usually the factors that the experimenter has hypothesized will have an effect on the system. The dependent variables are factors that are influenced by the independent variable. These are the variables that are being tested or measured in the experiment.
Often, a design will include a treatment group and a control group, which does not receive the treatment. Control variables are variables that are held constant in all treatment groups so that they do not affect the dependent variable.
For example, in an experiment investigating which type of fertilizer has the greatest effect on plant growth, the independent variable is the type of fertilizer used. The scientist is controlling, or manipulating, the type of fertilizer. The dependent variable is plant growth because the amount of plant growth depends on the type of fertilizer. The type of plant, the amount of water, and the amount of sunlight the plants receive are control variables because those variables of the experiment are kept the same for each plant.
Scientists often use models: a simplified representation of a system, such as a mathematical equation or a greenhouse. These models allow scientists to control and monitor the experiment’s inputs and outputs.
When designing an experiment, scientists must identify possible sources of error. These can be confounding variables, which are factors that act like the independent variable and thus can make it appear that the independent variable has a greater effect than it actually does. The design may also include unknown variables that are not controlled by the scientists. Finally, scientists must be aware of human error, particularly in collecting data and making observations, and of possible equipment errors.
During the experiment, scientists collect data, which must then be analyzed and presented appropriately. This may mean running a statistical analysis on the data (e.g., finding the mean) or putting the data in graph form. Such an analysis allows scientists to see trends in the data. From that data, scientists can draw a conclusion about the experiment.
The results that stem from an investigation with experimental and control variables are collectively known as scientific evidence. The evidence is then analyzed and used to draw conclusions based on whether or not it supports or counters the original hypothesis. The conclusions are then communicated to the scientific community. Evidence is not known as scientific proof; unlike mathematical proofs, scientific conclusions and evidence are not accepted as final proven knowledge.
Scientific facts, theories, and laws are terms with specific, distinct definitions. Scientific facts are objective observations that have been repeatedly confirmed by data collected by multiple scientific investigations. Facts are generally accepted as truth, but they are never considered final proof. Facts are the observations themselves, rather than the explanations for a natural phenomenon.
Hypotheses that are tested and confirmed repeatedly are theories: explanations that are supported by large amounts of data from multiple sources. Unlike the everyday definition of theory, which suggests just an idea, a scientific theory is widely accepted as a valid explanation of phenomena.
Scientific laws, unlike theories, are not explanations of phenomena but rather a generalized description of natural phenomena based on multiple observations over time. Laws are distinguished from facts by their durability—or ability to stay constant over time—and their predictive nature. If multiple investigations are run under the exact same conditions time and time again, the new observations will conform to the scientific law. If results are not as predicted, then the law can be modified and narrowed to incorporate the new information.