Six Basic Terms (All definitions are from https://www.merriam-webster.com/)
The language of chemistry (and all science) includes terms that specify the validity or degree of certainty of a statement. The following six terms encompass the wide range of certainty that scientist place upon their statements:
Fact – “a thing done; something that has actual existence; an actual occurrence”
Data - (plural) "collected by observation or measurement" What scientists gather as they do experiments. You must remember that although the number you measure is a fact, it may not be a true measure of what you think you are measuring. Also, all data are subject to scrutiny by other scientists (peer review) who may spot errors or inconsistencies. Most data undergoes some type of statistical analysis before it is used.
Assumption – “the supposition that something is true.” Not an observed or measured piece of data or a fact. Scientists use well-grounded assumptions to simplify calculations and to take into account immeasurable quantities. Assumptions can be “good” or “bad” depending on how many facts you have to back them up and show their validity.
Law – “a statement of an order or relation of phenomena that so far as is known is invariable under given conditions; a relation proved or assumed to hold between mathematical or logical expressions; the observed regularity of nature.” How scientists describe quantifiable (measurable) events or processes such as the law of gravity, the law of conservation of matter and Newton’s three laws of motion.
Model – “a description or analogy used to help visualize something that cannot be directly observed; a system of postulates, data, and inferences presented as a description of an object or an event.” What scientists use to describe objects or systems of study such as atomic and molecular structure, chemical reactions, evolutionary changes, patterns of global warming, etc. Models are also useful in predicting likely possible future events. The usefulness of a model depends on the strength of the data and assumptions that are used to create it.
"All models are wrong, but some models are useful." - George Box
Theory – “the analysis of a set of facts in their relation to one another; a plausible or scientifically acceptable general principle or body of principles offered to explain phenomena.” How scientists combine data (facts) and assumptions (well - educated guesses) to describe complex systems of nature such as atomic theory, wave/particle theory of light, evolutionary theory, plate tectonics theory.
Probability –“the mathematical study of the chance that a given event will occur." The true basis for predicting likely possible future events. For instance, chemists gather data,carry out statistical analysis of these data and then determine the probability of a chemical reaction occurring. Probability is also used to create and test models and theories.
All models and theories are subject to constant testing and will be altered or replaced if experimental data expose any flaws.
The Scientific Method
The Scientific Method is simply a framework for the systematic exploration of patterns in our world. It just so happens that this framework is extremely useful for the examination of chemistry and its many questions. The scientific process, an iterative process, uses the repeated acquisition and testing of data through experimental procedures to disprove hypotheses. A hypothesis is a proposed explanation of natural phenomena, and after a hypothesis has survived many rounds of testing, it may be accepted as a theory and used to explain the phenomena in question. Thus, the scientific method is not a linear process of steps, but a method of inductive reasoning.
In terms of science, the scientific method is a process used to step through the task of examining patterns in the world, forming a hypothesis that explain these patterns, and then gathering data to test the hypothesis. This time tested method has been applied in almost every field of inquiry such as physics, astronomy, chemistry, biology and ecology. "No one person can be credited as the inventor of the scientific method. It was really not invented but recognized and developed as the natural method of obtaining reliable knowledge" (Scientific Method History). Many of the method's attributes can be traced back to the works of Galileo in astronomy, Francis Bacon in philosophy, Robert Boyle in chemistry and physics, and Isaac Newton's work in physics. The goal of a using scientific method is to ultimately establish a natural law, which is a detailed statement about natural phenomena supported by a number of experiments.
The Scientific Method Explained
Here we will explore examples of how the scientific method is implemented. In reality, the Scientific Method is a complicated process that can take many directions and starting points. It is often referenced to be a iterative/recursive process because "An iterative process is a process for calculating a desired result by means of a repeated cycle of operations. An iterative process should be convergent, i.e., it should come closer to the desired result as the number of iterations increases" (Principia Cybernetica Web). Therefore, scientists often develop paradigms, which are patterns of thinking. These patterns of thinking often shift during the course of an experiment, so paradigms constantly shift. This is why the scientific method is usually more complex than the linear design below, but this just gives a general idea of the concept. In the diagram below, the process begins with a question. Second, the investigator will gather information and an initial understanding of their system in order to fully explore this question. Once there is enough evidence, a hypothesis will be formulated. A well-designed experiment will then be performed to produce the data required to approve or disprove the hypothesis in a defensible manner. If the data fails to disprove the hypothesis, then a new understanding of the system is produced and the process may need to start over again with a newly formed hypothesis. The method of inductive and deductive reasoning is also used through out this process. Inductive reasoning, is a type of logic in which natural laws or statements are inferred from observations. Facts are used to produce theories that explain patterns and indicate some degree of support (Wikipedia). Inductive reasoning is sometimes confused with deductive reasoning. Deductive logic is an analysis where reasoning is based on the validity and soundness of an argument. Thus, deductive reasoning draws conclusions on the basis of proofs, not merely by assuming or thinking about a predetermined clause (Buzzle.com). Both processes differ with regard to the standards of evaluation that are applicable to them. It may also be helpful to compare the Scientific Method and it's examples with that of Pseudo-Science.
Examples of Inductive Reasoning:
- 90% of humans are right-handed
- All swans are white
- Every life form we know of depends on water for survival
Examples of Deductive Reasoning:
- All men are mortal
- All apples are fruit
- All bachelors are single
What is a Theory?
Now that you have a general idea of how the scientific method works, it is important to understand what a theory is before we move to a more developed explanation of the method. The distinction of how a hypothesis becomes a theory is not clear. It is an ambiguous distinction of when a working hypothesis has survived testing from different approaches and explains a certain phenomena. A quote from the American Association for the Advancement of Science best describes this:
A scientific theory is a well-substantiated explanation of some aspect of the natural world, based on a body of facts that have been repeatedly confirmed through observation and experiment. Such fact-supported theories are not "guesses" but reliable accounts of the real world. The theory of biological evolution is more than "just a theory." It is as factual an explanation of the universe as the atomic theory of matter or the germ theory of disease. Our understanding of gravity is still a work in progress. But the phenomenon of gravity, like evolution, is an accepted fact.
Quite simply, a hypothesis is a prediction of what one believes may happen. This hypothesis becomes a theory when it is proven true (generally numerous times).
Also consider the Valence-Shell Electron-Pair Repulsion (VSEPR) Theory. This concept explains the geometric shape of bonded atoms and has been tested over and over again. The phenomenon of atomic bonding is indisputable, yet the VSEPR theory explains this well and has few exceptions.
The Scientific Method Break-Down
Now, let's explore this process as defined in this model. As you can see, the scientific process is not linear, but somewhat circular. This entails you to go back and revise and retest your hypothesis and experiments. Because the Scientific Method is not a linear process, we will describe each step as a series of phases.
Phase A: Ask a Question
In this first important phase, use the information you have to identify a pattern and ask a question. This may be in the form of a sentence followed by a question.
Example 1) I know that this material is a solid and conducts electricity. Is it comprised of more than one element?
Example 2) I know that apples fall from trees, dust settles from the air, the earth revolves around the sun and things generally fall down. Is there a fundamental force in nature that draws two objects together in proportion to their mass?
Example 3) I know that owls live in this forest and that two species of rabbit also live in this forest. I also know that owls eat rabbits. Do the owls in this forest have a preference to the species of rabbit they eat?
Often an investigator will gather some information before extensively gathering data in order to ask a question. Questions of How, What, When, Who, Why, or Where are commonly accompanied by observations.
Phase B: Gather Data/ Identify a Pattern/ Conduct Research
An investigator usually can approach their study system (the chemistry lab, an ecosystem, an astronomical phenomena or a new dataset) with an initial understanding forming the core of their study, and a peripheral question at the edge of their knowledge. Thus, investigators usually have some prior knowledge of their system in the form of small amounts of data or firsthand experience. This is not always the case however. It is not uncommon for a researcher to approach a system with no prior knowledge. And in this case, the prior knowledge would come after some researching of literature, interviews or anything else in that nature. Once a familiarity has been established, this usually leads to noticing patterns or processes that may be interesting to study. Let's introduce three examples:
Example 1) A scientist has been working in a laboratory and finds a substance in a drawer in an unmarked vial. She takes the material out and examines it visually. Curious of it's composition, she determines that it is a solid and then checks to see if it conducts electricity, and it does.
Example 2) A 15th century naturalist enjoys walking in the meadow surrounding his farm. One day he sees an apple fall from the tree and begins thinking about the process that leads to objects falling down and how that might apply to the world in general.
Example 3) A college student is meandering through a forest just after sunset walking her dog. Often, in this forest, her dog will get lucky and find a rabbit to chase. Sometimes the rabbit is gray and small. Other times, the rabbit is white and large. One night, she hears an owl screech in the distance.
In these instances, curious people noticed something about their worlds and began thinking about the patterns or processes that may have lead to the phenomena they experienced. In all cases, they decided to explore their systems further. So, they asked a question and did further extensive research.
Phase C: Form a Hypothesis, but What Exactly is a Good One?
A good hypothesis will provide a "tentative explanation for an observation that can be tested for further investigation" (The Free Dictionary). The hypothesis should be constructed so that it can help answer the questions that you have established in the previous step (The Free Dictionary). In our examples, the investigators could now form testable hypothesis that explain the patterns in question. The hypothesis should be in the form of a statement that is easily disproved in light of the proper information.
Example 1) Hypothesis: The material in the vial is comprised of two elements, copper and zinc.
Example 2) Hypothesis: There is a fundamental force in nature that attracts two objects to each other with a force in proportion to their mass.
Example 3) Hypothesis: Owls in this forest have no preference in the species of rabbits they eat.
These hypotheses are definitive statements explaining patterns the investigators have detected. The hypothesis is testable and can be disproved with information gathered during subsequent experiments. In this case, one thing leads to another, which produces results.
Phase D: Conduct Experiments
The experimental phase is where one may test their information to see if the hypothesis is true or false. Experimental design is a crucial component of the Scientific Method because it determines whether the hypothesis is just a prediction or theory. Proper studies should focus on the variable in question and produce data specific to the hypothesis. Scientists often keep journals and data tables to keep track of their observations. Methods of data analysis can vary, ranging from simple plots of trends to complex statistical analysis.
Example 1) To test the hypothesis that the material is composed to two metals, she heats the substance until it turns to a gas and notes the temperatures of the phase shift. After plotting the data in a graph, she notices that the phase shift occurs at two temperatures coinciding with the phase shifts of copper and zinc.
Example 2) This investigator performs no experiments. Instead he applies the concepts of his hypothesis to mathematically explain the elliptical orbits of planets. While at it, he also develops three laws of physics which help him explain this phenomena. These mathematical formulas are successfully applied to explain many different systems ranging from objects falling from buildings to planets orbits the sun.
Example 3) The investigator examines the owl pellets at 10 known owl nests. Looking at the differences of skeleton size and fur color to determine the rabbit species consumed, she notes the number of each species at each nesting site. Plotting the data in a 10 separate graphs, she determines that some owls definitely prefer the smaller rabbits while others clearly show a preference for the larger ones.
In an experiment, there will be variables. These variables are either influenced (independent variables) or reacting (dependent variables). An independent variable will change, and a dependent variable changes as a result of change in the manipulated variable. There is also a control variable that keeps things the same. Here is an example of this:
Spongebob and his Bikini Bottom pals have been busy doing a little research. Read the description for each experiment and answer the questions.
Krusty Krabs Breath Mints
Mr. Krabs created a secret ingredient for a breath mint that he thinks will "cure" the bad breath people get from eating crabby patties at the Krusty Krab. He asked 100 customers with a history of bad breath to try his new creation. He had fifty customers (Group A) eat a breath mint after they finished eating a krabby patty. The other fifty (Group B) also received a breath mint after they finished the sandwich. (However, the mint that Group B received was just a regular breath mint that did not have the secret ingredient). Both groups were told that they were getting the breath mint that would cure their bad breath. Two hours after eating the crabby patties, thirty customers in Group A and ten customers in Group B reported having better breath than they normally had after eating crabby patties.
- Which people are the control group?
- What is the independent variable?
- What is the dependent variable?
- What should Mr. Krabs' conclusion be?
- Why do you think 10 people in Group B reported fresher breath?
- Group B
- Group A
- Breath freshness
- The secret ingredient worked
- Placebo effect
Phase E: Analyze Results and Draw Conclusions / What Can be Said About the Hypothesis?
This phase is where the iterative nature of the scientific method comes from. After performing an experiment and analyzing the data, the scientist determines if the data produced disprove their hypothesis. As noted previously, it is important to understand that an experiment can never prove a hypothesis; rather it can only disprove one. If the hypothesis is disproved then the scientist can usually use the data produced from the experiment to construct a second hypothesis and then perform additional experiments building off the original hypothesis. Let's see what our three examples have done.
Example 1) Here, chemists hypothesis was that a substance was composed of two metals, copper and zinc. She performed an experiment whereby the data produced would clearly indicate if the two metals were not copper and zinc. While the data suggest (and is highly likely) that the two metals are indeed copper and zinc, and thus the substance is brass, she should perform an additional experiment.
Example 2) In this case, the scientist has performed no experiments. Rather he produced a mathematical system to explain his hypothesis and found that all things measured conform to this hypothesis. This hypothesis survived longer than the initial scientist and was later tested and applied to many other systems. In this case the hypothesis has advanced to the level of a theory. That is, it has survived many attempts to disprove it.
Example 3) Here, the investigator gathered data that showed that some owls clearly prefer small rabbits while others prefer larger rabbits. These data disproved her original hypothesis that the owls have no preference. Thus, using the data from the experiment, she could probably safely accept the hypothesis that owls have a preference for the size of rabbit they eat, and possibly take the next step to produce a new hypothesis. Two questions arise that may lead to a new hypothesis. Are there differences in the owls based on their rabbit preference (older owls eat the smaller rabbits, only male owls eat small rabbits, etc) or is there a difference in the distribution of the rabbits (only small rabbits are in the east side of the forest, etc.).
If the hypothesis is formulated appropriately, and the analyzed data are correct, the hypothesis may be considered correct and reported as a theory. If the hypothesis is not true, testing will have to be constructed again.
Phase F - Report Results
After all of the data are collected from an experiment and a theory is produced, results can then be communicated to the public or put into scientific research journals. It is interesting to think that any individual can develop and report the scientific method process just as a professional scientist would do.
Even though we show the scientific method as a series of steps, keep in mind that new information or thinking might cause a scientist to back up and repeat steps at any point during the process. A process like the scientific method that involves such backing up and repeating is similar to an iterative process. The scientific method is an important part of life and a grander plan that formulates a lot of theories.
- AAAS Evolution Resources
- http://pespmc1.vub.ac.be/ASC/ITERAT_PROCE.html (Iterative Process)
- Petrucci, Ralph. Harwood, William. Herring, Geoffrey. Madura, Jeffery. GENERAL CHEMISTRY Principles and Modern Applications 9th Edition. Macmillan Publishing co, New Jersey. 1989.
- Campbell, Neil A. BIOLOGY Fourth Edition. The Benjamin/Cummings Publishing Company, Inc. 1996
1.) True or False: The Scientific Method is a linear process with a discrete start and end.
2.) True or False: An experiment can prove a hypothesis. Why?
3.) Why is it difficult to explain how a hypothesis becomes a theory?
4.) Why is the scientific method sometimes called an iterative process?
1) False. The Scientific Method is an iterative process that repeats, stops and starts in different phases depending on the application
2) False. An experiment can only falsify a hypothesis. A quote by Albert Einstein sums it up. "No amount of experimentation can ever prove me right; a single experiment can prove me wrong."
3) It is difficult to explain how a hypothesis becomes a theory because one has to understand what exactly a hypothesis and theory are. A hypothesis is simply a prediction of what someone believes will happen. A hypothesis becomes a theory when it is proven true. If the hypothesis is proven false, it stays a hypothesis.
4) The scientific method is sometimes called an iterative process because it can take different routes after experimental data are collected. If the hypothesis is disproved, a new take will be beneficial in order to get effective answers. If the hypothesis is confirmed, the results will be reported. This is constantly a cause and effect technique because there are many causes and effects that influence the whole process.
Outside Practice Problems
- Harley Brinkman (UCD)
- Tom Neils (Grand Rapids Community College)