1.1: How Science Works

The Nature of Science

The word science comes from the Latin scientia, meaning knowledge. Science can be defined as knowledge about the natural world. Science is a very specific way of learning, or knowing, about the world. It involves asking questions about the world around you and then pursuing the answer using a process called the scientific method, which we will discuss in a later section. By following the steps in this method, scientists can make amazing discoveries about how the universe works. But the discovery is not the end of the process. It must be shared with others and be tested and revised over and over again. Science is never completely done. This textbook contains a progress report of what we know about the universe, with many open questions that scientists are working on right now.

The knowledge that people have gained from science has made many fundamental changes to how people live. However, there are areas of knowledge and human experience that the methods of science cannot be applied to. These include such things as answering purely moral questions, aesthetic questions, or what can be generally categorized as spiritual or religious questions. Science cannot investigate these areas because they are outside the realm of material phenomena, the phenomena of matter and energy, and cannot be observed and measured. Always remember that science can tell you how the universe formed and how it works, but it can't tell you why the universe exists.

The Natural Sciences

There are many different types of science. There are the formal sciences which includes fields like statistics and computer science. The social sciences include economics and anthropology. Astronomy is one of the natural sciences, a group that includes biology, chemistry, earth science, and physics. Other scholars choose to divide natural sciences into life sciences, which study living things and include biology, and physical sciences, which study nonliving matter and include astronomy, physics, and chemistry. Some disciplines such as biophysics and biochemistry build on two sciences and are interdisciplinary.

Scientific Inquiry

One thing is common to all forms of science: an ultimate goal to know. Curiosity and inquiry are the driving forces for the development of science. Scientists seek to understand the world and the way it operates. Two methods of logical thinking are used: inductive reasoning and deductive reasoning.

Inductive reasoning is a form of logical thinking that uses related observations to arrive at a general conclusion. This type of reasoning is common in descriptive science. A life scientist such as a biologist makes observations and records them. These data can be qualitative or quantitative. Qualitative data includes descriptions, and can be subjective, which means two scientists might describe the same thing in different ways. Quantitative data uses numbers and is usually objective. If two scientists weigh the same rock, they will most likely get the same number. A scientist using inductive reasoning will gather all of their evidence, both qualitative and quantitative, and make conclusions based on all of the evidence. Inductive reasoning involves formulating generalizations based on careful observation and the analysis of a large amount of data.

Deductive reasoning or deduction is the type of logic used in hypothesis-based science. In deductive reasoning, the pattern of thinking moves in the opposite direction as compared to inductive reasoning. Deductive reasoning is a form of logical thinking that uses a general principle or law to forecast specific results. From those general principles, a scientist can predict the specific results that would be valid as long as the general principles are valid. For example, a prediction would be that if someone threw a ball off of a tower, it would fall to the ground. Most people would be able to make this prediction based on their life experience. Scientific prediction makes more complicated predictions based on past observations, such as predicting the position of an undetectable source of gravity.

The boundary between these two forms of study is often blurred, because most scientific research combines both approaches. Scientists use both of these types of reasoning depending on their source of data.

The Scientific Method

As scientists inquire and gather information about the world, they follow a process called the scientific method. This process typically begins with an observation and question that the scientist will research. Next, the scientist typically looks for information about the topic and then devises a hypothesis. Then, the scientist will test the hypothesis by performing an experiment. Finally, the scientist analyzes the results of the experiment and draws a conclusion. Note that the scientific method can be applied to many situations that are not limited to science, and this method can be modified to suit the situation.

Consider an example. Let us say that you try to turn on a car, but it will not start. You probably wonder: Why will the car not start? You can follow a scientific method to answer this question. First off, you might try to find some information about reasons why a car will not start. Next, you will state a hypothesis. For example, you may believe that the car is not starting because it has no engine oil. To test this, you open the hood of the car and examine the oil level. You observe that the oil is at an acceptable level, and you thus conclude that the oil level is not contributing to your car issue. To troubleshoot the issue further, you may devise a new hypothesis to test and then repeat the process again.

The scientific method is often shown as a flowchart that ends in knowledge. In reality, scientists usually find an answer to their question along with several new questions to pursue. The scientific method is more like a circle, like in Figure \(\PageIndex{1}\), that goes through the six steps: 1. make an observation and ask a question, 2. research the topic, 3. form a hypothesis, 4. perform an experiment, 5. analyze the data, 6. and share the results which leads to new observations and questions. The next sections will go into each of these steps in more detail.

Figure \(\PageIndex{1}\) : The Scientific Method. The six steps of observation, research, hypothesis, experiment, analysis, and reporting conclusions form a repeating cycle rather than a straight path to a final answer. (CC BY-SA 4.0; Efbrazil via Wikimedia Commons) Accessible description of Figure \(\PageIndex{1}\).

Observation/Question

The scientific process typically starts with an observation, often a problem to be solved, that leads to a question. Let's use an astronomy observation as an example. Imagine that we are astronomers in the early 1900s. We collect some light from the Sun, making an observation, and notice that there are some strange gaps in the light. We might wonder: What are these strange gaps in the light from the Sun? Now it's time to do a little research and learn more about the Sun and light.

Research

Sometimes when we ask a question about something we see in the world, we can just look up the answer. Right now, astronomers know exactly why our observations look the way they do, and more importantly, what the data means about the Sun. However, in our example the scientific community in the early 1900s didn't have those answers. Continuing our example, we try to learn more about the Sun and its light by doing some research using trusted sources of information, such as research papers published by other astronomers. We find studies that talk about observations of stars that have weird gaps in their light, and others about similar gaps in light that moves through a gas in laboratory experiments. Now that we understand more about stars and light, we can form a hypothesis.

Hypothesis

After doing the research, a scientist will try to answer their question. In our example, we wanted to know why our observation of the Sun had gaps in its light. We learned that stars also have gaps in their light and that light that passes through a gas in the lab also has gaps. From the observations and information, we might think that the Sun and other stars are made of a gas. That is our hypothesis.

A hypothesis is a reasonable explanation of the observations that is testable. It would be unreasonable to propose that the Sun was made of lava, because there was nothing in our observations or research that suggested lava. A hypothesis must always make sense considering the data and our current understanding of science. Testing a hypothesis involves making a prediction. A prediction is similar to a hypothesis but it typically has the format “If . . . then . . . .” For example, the prediction for our hypothesis could be, “If the Sun is made of gas, then the light from the Sun should match the light from the same gas in the lab.”

At this point, it does not matter if our hypothesis is right or wrong, or falsifiable. An example of an unfalsifiable hypothesis is “Botticelli's Birth of Venus is beautiful.” Opinions are not falsifiable. A hypothesis can be tested using experiments, calculations, new observations, or comparison to someone else's results. If the person that formulates the hypothesis does not have the equipment to test it, the hypothesis is still valid. Some hypotheses can't be tested with our current level of technology. This kind can still be valid as long as it proposes a test that can possibly be done some day. Some hypotheses have waited hundreds of years to be tested. An untestable hypothesis would be one that made an unmeasurable prediction that could not be proven or disproven. For example, a hypothesis that depends on what a bear thinks is not testable, because it can never be known what a bear thinks.

If there is more than one reasonable explanation for the observation, there can be multiple hypotheses that are all valid as long as they can be independently tested. To test a hypothesis, a researcher will conduct one or more experiments designed to eliminate one or more of the hypotheses. This is important. A hypothesis can be disproven, or eliminated, but it can never be proven. Science does not deal in proofs like mathematics. If an experiment fails to disprove a hypothesis, then the hypothesis is still valid. For any hypothesis in science, it is possible that some future experiment or observation will falsify it. To describe how the universe works, scientists rely on the best hypothesis, or explanation, until it is falsified. Then we either adjust the hypothesis to also explain the new result, or we create a new hypothesis that is a better explanation.

Experiment

To test a hypothesis, scientists must carefully design an experiment to test it. If the tests are randomly selected, they won't be able to disprove the hypothesis. Ideally, an experiment has only one aspect of it that changes, called a variable. All other aspects of the experiment are called controls, and should remain the same. In reality, experiments usually have more than one variable, since it can be a challenge to keep everything constant. Keep in mind that experiments do not always occur in a lab. Sometimes the experiment is observing many different types of stars and comparing them to each other. Sometimes the experiment is creating a computer model that simulates the formation of a star and comparing the model results to observations.

Imagine that in our example, we have access to a lab where we can collect light moving through two different types of gas. The available gases are neon and argon. As long as we use the same light source for each sample, our variable is the type of gas. We also have two more specific hypotheses: "The Sun is made of the gas neon," and "the Sun is made of the gas argon." We are able to collect light from both types of gases. The next step is to analyze our data, but before we do that, we need to make sure that our data is accurate.

Data and Experimental Error

During an experiment, a scientist collects data. The data might be measurements that are recorded on paper or digitally. Even if the scientist is very careful it is possible to make a mistake. One kind of mistake is with the equipment. For example, an electronic balance, or scale, may always measure one gram high. To fix this, the balance should be adjusted. If it can't be adjusted, each measurement should be corrected. A mistake can come if a measurement is hard to make. For example, the scientist may stop a stopwatch too soon or too late. To fix this, the scientist should run the experiment many times and make many measurements. The average of the measurements will be the accurate answer. Sometimes the result from one experiment is very different from the other results. If one data point is really different compared to many other data points, it may be thrown out. It is likely a mistake was made in that experiment. These are all examples of experimental error and methods that scientists use to ensure that their data is as accurate as possible.

Analysis

The scientist must next form a conclusion. The scientist must study all of the data, except for the data excluded by errors. What statement best explains the data? Did the experiment prove the hypothesis? Sometimes the experimental results agree with the hypothesis. Other times the data disproves the hypothesis. Sometimes it's not possible to tell. If there is no conclusion, the scientist may test the hypothesis again using different experiments. No matter what, the experiment shows the scientist has learned something. Even a disproved hypothesis can lead to new questions.

After making careful and repeated measurements of the light passing through neon and argon, we are ready to analyze our experimental results by comparing them to observations of the Sun. Unfortunately, the gaps don't match up for either gas. We have disproven our two hypotheses that the Sun is made of neon or argon. However, we have not disproven that the Sun is made of another type of gas. Our overall hypothesis that the Sun is made of a gas, is still valid and testable since we did not test every gas in nature. We can then form new hypotheses for different gases and test those as well, restarting the steps of the scientific method. However, we should share our results so others know that the Sun is neither argon nor neon.

Reporting Scientific Work

Scientists must share their findings for other researchers to expand and build upon their discoveries. Communication and collaboration between scientists are key to the advancement of knowledge in science. For this reason, an important aspect of a scientist's work is reporting results and communicating with peers. Scientists can share results by presenting them at a scientific meeting or conference, but this approach can reach only the limited few who are present. Scientists also publish their results in peer-reviewed articles that are part of scientific journals. Peer-reviewed articles are scientific papers that are reviewed, usually anonymously by a scientist's colleagues, or peers. These colleagues are qualified individuals, often experts in the same research area, who judge whether or not the scientist's work is suitable for publication. The process of peer review helps to ensure that the research described in a scientific paper is significant, logical, and thorough. Scientists publish their work so other scientists can reproduce their experiments under similar or different conditions to expand on the findings. In this way, a hypothesis can be tested in many different ways by many different people. If a hypothesis survives a large amount of testing, scientists may start referring to it as a theory.

Theories

When one scientific research paper is published, it often inspires many other papers to be published on the same topic. The evidence for or against a hypothesis is discussed by many scientists. Sometimes a hypothesis is repeatedly shown to be true and never shown to be false. If a hypothesis turns out to be capable of explaining a large body of experimental data, it can reach the status of a theory. Scientific theories are well-substantiated, comprehensive, testable explanations of particular aspects of nature. Theories are accepted by the scientific community because they provide satisfactory explanations, but they can be modified if new data become available.

In science, a theory has been repeatedly shown to be the best explanation for the data. A theory is supported by many observations. However, a theory may be disproved if conflicting data is discovered. Many important theories have been shown to be accurate by many observations and experiments and are extremely unlikely to be disproved.

Laws

A scientific law uses concise language to describe a pattern in nature that is supported by scientific evidence and repeated experiments. Often, a law can be expressed in the form of a single mathematical equation. Laws and theories are similar in that they are both scientific statements that result from a tested hypothesis and are supported by scientific evidence. However, the designation law is reserved for a concise and very general statement that describes phenomena in nature, such as the law that energy is conserved during any process. A theory, in contrast, is a less concise statement of observed phenomena. For example, the theory of evolution requires a long explanation to clearly express its meaning. It also can't be described with a single equation. The biggest difference between a law and a theory is that a theory is much more complex and dynamic. A law describes a single action, whereas a theory explains an entire group of related phenomena.

One major assumption in astronomy is that the laws of nature work the same way in all parts of the universe. Without the existence of such universal laws, we could not make much progress in astronomy. If each pocket of the universe had different rules, we would have little chance of interpreting what happened in distant regions of space. But, the consistency of the laws of nature gives us enormous power to understand distant objects without traveling to them.

Models

Scientists often use models to explain processes in science. A model is a representation of something that is often too difficult to display directly. Some models are something that you can see or touch. Other types of models use an idea or numbers. Each type is useful in certain ways. While a model is justified with experimental proof, it is only accurate under limited situations. The real situation is usually more complicated, but the model represents the general idea of how things work. Models also help scientists to make predictions about complex systems. Astronomers can use a computer model to simulate a physical process, such as the formation of a star, that can be compared to observations of star formation.

Physical Models

A physical model is a representation of something using objects. It can be three-dimensional, like a globe. It can also be a two-dimensional drawing or diagram, such as a map. Models are usually smaller and simpler than the real object. They most likely leave out some parts, but contain the parts that help explain the process. In a good model the parts are made or drawn to scale. Physical models allow us to see, feel and move their parts. This allows us to better understand the real system.

An example of a physical model is a drawing of the layers of Earth. A drawing helps us to understand the structure of the planet. Yet there are many differences between a drawing and the real thing. The size of a model is much smaller, for example. A drawing also doesn't give a good idea of how substances move. Arrows showing the direction the material moves can help. A physical model is very useful but it can't explain the real Earth perfectly.

Ideas as Models

Some models are based on an idea that helps scientists explain something. A good idea explains all the known facts. An example is how Earth got its Moon. A Mars-sized planet hit Earth and rocky material broke off of both bodies. This material orbited Earth and then came together to form the Moon. This is a model of something that happened billions of years ago. It brings together many facts known from our studies of the Moon's orbit and surface. It accounts for the chemical makeup of rocks from the Moon, Earth, and meteorites. It has been simulated many times using computer models. The physical properties of Earth and Moon figure in as well. So far some of the data match the model, but if new data disagrees with the model it will have to be changed or discarded, similar to a hypothesis.

Models that Use Numbers

Models may use formulas or equations to describe something. Sometimes math may be the only way to describe it. For example, equations help scientists to explain what happened in the early days of the universe. The universe formed so long ago that math is the only way to describe it. A climate model includes lots of numbers, including temperature readings, ice density, snowfall levels, and humidity. These numbers are put into equations to make a model. The results are used to predict future climate. For example, if there are more clouds, does global temperature go up or down? Models are not perfect because they are simple versions of the real situation. Even so, these models are very useful to scientists, and they can be constantly refined after comparison to observations.

Summary of Scientific Process

In practice, the scientific method is not as rigid and structured as it might at first appear. Sometimes an experiment leads to conclusions that favor a change in approach; often, an experiment brings entirely new scientific questions to the puzzle. Many times, science does not operate in a linear fashion; instead, scientists continually draw conclusions and make generalizations, finding patterns as their research proceeds. Scientific reasoning is more complex than the scientific method alone suggests. Scientific progress requires more than just the individual experiments performed to test a hypothesis. Science only works if research is constantly shared with the rest of the community, inspiring new experiments and collaborations. It is an endless, cooperative project that humanity continues to work on together.

Figure \(\PageIndex{2}\) demonstrates how the scientific method fits into the larger practice of science. The observation and curiosity of scientists produce new hypotheses that are tested and the results are shared with the community. If the hypothesis repeats the cycle through the community it may eventually become a law or theory.

Figure \(\PageIndex{2}\) : How Science Works. Repeated cycles of hypothesis testing and peer feedback allow well-supported hypotheses to become theories and consistent patterns to become laws. (CC BY 4.0; OpenStax via Wikimedia Commons) Accessible description of Figure \(\PageIndex{2}\).

Examples and Exercises

Example: The Scientific Method

In the example below, the scientific method is used to solve an everyday problem. Which part in the example below is the hypothesis? Which is the prediction? Based on the results of the experiment, is the hypothesis supported? If it is not supported, propose some alternative hypotheses.

1. My toaster doesn't toast my bread.
2. Why doesn't my toaster work?
3. There is something wrong with the electrical outlet.
4. If something is wrong with the outlet, my coffeemaker also won't work when plugged into it.
5. I plug my coffeemaker into the outlet.
6. My coffeemaker works.

Solution

The hypothesis is #3 (there is something wrong with the electrical outlet), and the prediction is #4 (if something is wrong with the outlet, then the coffeemaker also won't work when plugged into the outlet). The original hypothesis is not supported, as the coffee maker works when plugged into the outlet. Alternative hypotheses may include (1) the toaster might be broken or (2) the toaster wasn't turned on.