The Steps scientific method Serve to answer a scientific question in an organized and objective manner. It involves observing the world and its phenomena, arriving at an explanation of what is observed, testing whether the explanation is valid, and finally accepting or denying the explanation.
Therefore, the most important features of the scientific method are observation, experimentation, and asking and answering questions. However, not all scientists follow this process exactly. Some areas of science may be more easily tested than others.
Question, observation, hypothesis, experiment, data analysis, conclusions.
For example, scientists who study how stars change as they age or how dinosaurs digest their food can not advance the life of a star in a million years or conduct studies and tests with dinosaurs to test their hypotheses.
When direct experimentation is not possible, scientists modify the scientific method. Although it is modified with almost every research, the goal is the same: to discover cause and effect relationships by asking questions, collecting and examining data, and seeing if all available information can be combined into a logical response.
On the other hand, the scientific method is often iterative; New information, observations or ideas may cause the steps to be repeated again.
The protocols of the scientific method can be divided into six steps:
- Question
- Observation
- Formulation of the hypothesis
- Experimentation
- Analysis of data
- Reject or accept the hypothesis.
Below I will show you the fundamental steps that are taken when doing an investigation. For you to understand better, at the end of the article I will leave how these steps were used in the discovery of the DNA structure.
What are the steps of the scientific method, what do they consist of and their characteristics?
Step 1- Ask a question
The scientific method begins when the scientist / researcher asks a question about something he has observed: How, what, when, who, what, why or where?
Step 2- Observation
This step consists in making observations and gathering information to help answer the question. The observations should not be informal, but intentional with the idea that the information collected is objective.
Systematic and careful collection of measurements and data is the difference between pseudosciences, such as alchemy, and sciences, such as chemistry or biology.
Measurements can be made in a controlled environment, such as a laboratory, or over more or less inaccessible or non-manipulable objects such as stars or human populations.
Measurements often require specialized scientific instruments such as thermometers, microscopes, spectroscopes, particle accelerators, voltmeters...
Step 3- Hypothesis Formulation
A hypothesis is a statement that can be used to predict the outcome of future observations. The null hypothesis is a good type of hypothesis to begin an investigation.
It is a suggested explanation of a phenomenon or a reasoned proposal that suggests a possible correlation between a set of phenomena.
An example of a null hypothesis is:"the speed at which grass grows does not depend on the amount of light it receives."
Examples of hypotheses:
- Soccer players who train on a regular basis using time, score more goals than those who lack 15% of days to practice.
- Newer parents who have studied higher education are in 70% of the more relaxed cases in childbirth.
A useful hypothesis must allow predictions by reasoning, including deductive reasoning. It could predict the outcome of an experiment in a laboratory or the observation of a phenomenon in nature. The prediction can also be statistical and deal only with probabilities.
If predictions are not accessible by observation or experience, the hypothesis is not yet testable and will remain to that unscientific extent. Later, a new technology or theory could make the experiments necessary.
Step 4- Experimentation
Case of experiment with humans.
Predictions that attempt to make the hypotheses can be checked with experiments. If the test results contradict the predictions, the hypotheses are questioned and become less sustainable.
If the experimental results confirm the predictions, then the hypotheses are considered to be more correct, but they may be wrong and remain subject to further testing.
Experimental control is a technique for treating observational error. This technique uses the contrast between multiple samples (or observations) under different conditions to see what varies or what remains the same.
For example, to test the null hypothesis"the growth rate of the herb does not depend on the amount of light", we would have to have grass that is not exposed to light.
This is called the"control group". They are identical to the other experimental groups, except for the variable being investigated.
They can be tested with many variables. In the case of grass and light: having different levels of light, different types of herbs, etc.
It is important to remember that the control group can only differ from any experimental group in one variable. That way you can know that it is this variable that produces changes or not.
For example, you can not compare the grass that is outside in the shade and the grass in the sun. Nor the grass of one city with that of another. There are variables between the two groups in addition to light, such as soil moisture and pH...
Step 5: Data Analysis
After the experiment, the data are taken, which can be in the form of numbers, yes / no, present / absent, or other observations.
It is important to take into account data that were not expected or not wanted. Many experiments have been sabotaged by researchers who do not take into account the data that do not match what is expected.
This step involves determining what the results of the experiment show and deciding what actions to take next. The predictions of the hypothesis are compared with those of the null hypothesis, to determine which is more able to explain the data.
In cases where an experiment is repeated many times, statistical analysis may be necessary.
If the evidence has falsified the hypothesis, a new hypothesis is required; If the experiment supports the hypothesis, but the evidence is not strong enough, other predictions of the hypothesis must be proved.
Once a hypothesis is strongly backed up by evidence, you may ask a new question to provide more information on the same topic.
Step 6: Interpret the data and accept or reject the hypothesis
For many experiments, the conclusions are formed on the basis of an informal analysis of the data. Just ask, does the data fit the hypothesis? Is a way of accepting or rejecting a hypothesis.
However, it is better to apply a statistical analysis to the data, to establish a degree of"acceptance"or"rejection". Mathematics is also useful for evaluating the effects of measurement errors and other uncertainties in an experiment.
If the hypothesis is accepted, it is not guaranteed to be the correct hypothesis. This only means that the results of the experiment support the hypothesis. It is possible to duplicate the experiment and get different results next time. The hypothesis may also explain the observations, but it is the wrong explanation.
If the hypothesis is rejected, it may be the end of the experiment or re-run. If the process is repeated, more observations and more data will be taken.
Other steps are: 7- Publish results and 8- Check the results by replicating the research (by other scientists)
If an experiment can not be repeated to produce the same results, this implies that the original results could have been erroneous. As a result, it is common for a single experiment to be performed several times, especially when there are uncontrolled variables or other indications of experimental error.
To get meaningful or surprising results, other scientists may also try to replicate the results for themselves, especially if those results are important to their own work.
Example of a scientific method in the discovery of the structure of DNA
The history of the discovery of the structure of DNA is a classic example of the steps of the scientific method: in 1950 it was known that genetic inheritance had a mathematical description, beginning with Gregor Mendel's studies, and that DNA contained genetic information.
However, the mechanism for storing genetic information (ie, genes) in the DNA was unclear.
It is important to note that the discovery of the DNA structure did not involve only Watson and Crick - although they were given the Nobel Prize. They brought knowledge, data, ideas and discoveries many scientists of the time.
Question
Previous DNA research had determined their chemical composition (the four nucleotides), the structure of each of the nucleotides and other properties.
He had been identified as the bearer of genetic information by the Avery-MacLeod-McCarty experiment in 1944, but the mechanism of how genetic information is stored in the DNA was unclear.
Observation and hypothesis
All that was investigated at that time on the DNA is the observations. In this case, observations were often made under a microscope or X-ray.
Linus Pauling proposed that DNA could be a triple helix. This hypothesis was also considered by Francis Crick and James D. Watson but discarded.
When Watson and Crick knew the Pauling hypothesis, they understood by the existing data was wrong and that Pauling would soon admit its difficulties with that structure. Therefore, the race to discover the DNA structure was in discovering the correct structure.
What prediction would make the hypothesis?
If the DNA had a helical structure, its X-ray diffraction pattern would be X-shaped. This prediction was a mathematical construction, completely independent of the biological problem at hand.
Therefore, the hypothesis that DNA has a double helix structure would be tested with X-ray data results, specifically X-ray diffraction data provided by Rosalind Franklin, James Watson and Francis Crick proposed in 1953.
Experiment
Rosalind Franklin crystallized pure DNA and performed X-ray diffraction to produce photo 51. The results showed an X-shape.
In a series of five articles published in Nature, the experimental evidence supporting the Watson and Crick model was demonstrated. Of these, the article by Franklin and Raymond Gosling was the first publication with X-ray diffraction data that supported the model of Watson and Crick
Analysis
When Watson saw the detailed diffraction pattern, he immediately recognized it as a propeller. He and Crick produced their model, using this information along with previously known information on DNA composition and on molecular interactions, such as hydrogen bonds.
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