What Is the Scientific Method?

Answer 1

Okay, you need to come up with a scientific research project or science fair project. One of the obvious challenges is to find an idea for the project. Also, you need science involved, so you will need to apply the scientific method somehow. The scientific method can be stated several ways, but basically it involves looking at the world around you, coming up with an explanation for what you observe, testing your explanation to see if it could be valid, and then either accepting your explanation (for the time being... after all, something better might come along!) or rejecting the explanation and trying to come up with a better one. If you are having trouble designing an experiment or even getting an idea for a project, start with the first step of the scientific method: make observations.

Step 1: Make Observations

A lot of people think that the scientific method starts with forming a hypothesis. The reason for this misconception may be because many observations are made informally. After all, when you are looking for a project idea, you think through all of the things you have experienced (observations you have made) and try to find one that would be suitable for an experiment. Although the informal variation of Step 1 works, you will have a richer source of ideas if you pick a subject and write down observations until a test-able idea comes up. For example, let's say you want to do an experiment, but you need an idea. Take what is around you and start writing down observations. Write down everything! Include colors, timing, sounds, temperatures, light levels... you get the idea.

Step 2: Formulate a Hypothesis

A hypothesis is a statement that can be used to predict the outcome of future observations. The null hypothesis, or no-difference hypothesis, is a good type of hypothesis to test. This type of hypothesis assumes no difference between two states. Here is an example of a null hypothesis: 'the rate at which grass grows is not dependent on the amount of light it receives'. Even if I think that light affects the rate at which my grass grows (probably not as much as rain, but that's a different hypothesis), it is easier to disprove that light has no effect than to get into complicated details about 'how much light', or 'wavelength of light', etc. However, these details can become their own hypotheses (stated in null form) for further experimentation. It is easiest to test separate variables in separate experiments. In other words, don't test the effects of light and water at the same time until after you have tested each separately.

Step 3: Design an Experiment

There are many different ways to test a single hypothesis. If I wanted to test the null hypothesis, 'the rate of grass growth is not dependent on quantity of light', I would have grass exposed to no light (a control group... identical in every way to the other experimental groups except for the variable being tested), and grass with light. I could complicate the experiment by having differing levels of light, different types of grasses, etc. Let me stress that the control group can only differ from any experimental groups with respect to the one variable. For example, in all fairness I could not compare grass in my yard in the shade and grass in the sun... there are other variables between the two groups besides light, such as moisture and probably pH of the soil (where I am it is more acidic near the trees and buildings, which is also where it is shady). Keep your experiment simple.

Step 4: Test the Hypothesis

In other words, perform an experiment! Your data might take the form of numbers, yes/no, present/absent, or other observations. It is important to keep data that 'looks bad'. Many experiments have been sabotaged by researchers throwing out data that didn't agree with preconceptions. Keep all of the data! You can make notes if something exceptional occurred when a particular data point was taken. Also, it is a good idea to write down observations related to your experiment that aren't directly related to the hypothesis. These observations could include variables over which you have no control, such as humidity, temperature, vibrations, etc., or any noteworthy happenings.

Step 5: Accept or Reject the Hypothesis

For many experiments, conclusions are formed based on informal analysis of the data. Simply asking, 'Does the data fit the hypothesis', is one way to accept or reject a hypothesis. However, it is better to apply a statistical analysis to data, to establish a degree of 'acceptance' or 'rejection'. Mathematics is also useful in assessing the effects of measurement errors and other uncertainties in an experiment.

Hypothesis Accepted? Things to Keep in Mind

Accepting a hypothesis does not guarantee that it is the correct hypothesis! This only means that the results of your experiment support the hypothesis. It is still possible to duplicate the experiment and get different results next time. It is also possible to have a hypothesis that explains the observations, yet is the incorrect explanation. Remember, a hypothesis can be disproven, but never proven!

Hypothesis Rejected? Back to Step 2

If the null hypothesis was rejected, that may be as far as your experiment needs to go. If any other hypothesis was rejected, then it is time to reconsider your explanation for your observations. At least you won't be starting from scratch... you have more observations and data than ever before!!

Answer 2

It is a systematic method at determining "the truth." There is an entire branch of philosophy, called epistomology, dedicated to figure out how we know what we know. In religion, for example, "God" or "gods" or "the voices inside my head" or "the Book" or "the books" are the sources of revelation.

In science, the standard method to arrive at a valid understanding is to propose an explanation based on what you know. This is called a hypothesis. You then test the hypothesis by doing experiments. These experiments can prove your hypothesis correct or incorrect, or just yield ambiguous results. If the results are ambiguous you do more experiments, but once you have determined whether your hypothesis was correct or not, you have advanced knowledge. You have either confirmed that your understanding that led to your original hypothesis is correct, or you have provided one piece of evidence to contradict the established understanding, thereby leading to better explanations and theories.

As an example: John Dalton's atomic theory stated that the atom was like a pudding, with things like protons floating in it (like fruit in a yogurt). Then Rutherford did his gold foil experiment, where he shot a stream of alpha particles at a very very thin layer of gold. Based on Dalton's theory at the time, Rutherford predict that most alpha particles would be deflected back, but in fact most of the particles went straight through. Since that observation was not consistent with Dalton's model, Rutherford then eventually worked to a different atomic model where most of the space in the atom is empty space.

You can read more about this as well as anything else at wikipedia: http://en.wikipedia.org/wiki/Scientific_method

Answer 3

a method of research in which a problem is identified, relevant data are gathered, a hypothesis is formulated from these data, and the hypothesis is empirically tested.
The scientific method includes: observing, classifying, estimating, measuring, predicting, infering, and actually experimenting......hope this helps

Answer 4

Scientific method is a body of techniques for investigating phenomena and acquiring new knowledge, as well as for correcting and integrating previous knowledge. It is based on gathering observable, empirical, measurable evidence, subject to specific principles of reasoning.[1]

Although procedures vary from one field of inquiry to another, there are identifiable features that distinguish scientific inquiry from other methods of developing knowledge. Scientific researchers propose specific hypotheses as explanations of natural phenomena, and design experimental studies that test these predictions for accuracy. These steps are repeated in order to make increasingly dependable predictions of future results. Theories that encompass wider domains of inquiry serve to bind more specific hypotheses together in a coherent structure. This in turn aids in the formation of new hypotheses, as well as in placing groups of specific hypotheses into a broader context of understanding.


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1 Elements of scientific method
1.1 DNA example
1.2 Characterizations
1.2.1 DNA/characterizations
1.2.2 Precession of Mercury
1.3 Hypothesis development
1.3.1 DNA/hypotheses
1.4 Predictions from the hypothesis
1.4.1 DNA/predictions
1.4.2 General relativity
1.5 Experiments
1.5.1 DNA/experiments
2 Evaluation and iteration
2.1 Testing and improvement
2.1.1 DNA/iterations
2.2 Confirmation
3 Models of scientific inquiry
3.1 Classical model
3.2 Pragmatic model
3.3 Computational approaches
4 Philosophy and sociology of science
5 Communication, community, culture
5.1 Peer review evaluation
5.2 Documentation and replication
5.3 Dimensions of practice
6 History
7 Notes and references
8 Further reading
9 See also
9.1 Synopsis of related topics
9.2 Logic, mathematics, methodology
9.3 Problems and issues
9.4 History, philosophy, sociology
10 External links
10.1 Science treatments
10.2 Alternative scientific treatments


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See link below

Answer 5

Solving a problem logically by following a definite procedure.

Answer 6

The scientific method is the process by which scientists, collectively and over time, endeavor to construct an accurate (that is, reliable, consistent and non-arbitrary) representation of the world.

Recognizing that personal and cultural beliefs influence both our perceptions and our interpretations of natural phenomena, we aim through the use of standard procedures and criteria to minimize those influences when developing a theory. As a famous scientist once said, "Smart people (like smart lawyers) can come up with very good explanations for mistaken points of view." In summary, the scientific method attempts to minimize the influence of bias or prejudice in the experimenter when testing an hypothesis or a theory.
I. The scientific method has four steps

1. Observation and description of a phenomenon or group of phenomena.

2. Formulation of an hypothesis to explain the phenomena. In physics, the hypothesis often takes the form of a causal mechanism or a mathematical relation.

3. Use of the hypothesis to predict the existence of other phenomena, or to predict quantitatively the results of new observations.

4. Performance of experimental tests of the predictions by several independent experimenters and properly performed experiments.

If the experiments bear out the hypothesis it may come to be regarded as a theory or law of nature (more on the concepts of hypothesis, model, theory and law below). If the experiments do not bear out the hypothesis, it must be rejected or modified. What is key in the description of the scientific method just given is the predictive power (the ability to get more out of the theory than you put in; see Barrow, 1991) of the hypothesis or theory, as tested by experiment. It is often said in science that theories can never be proved, only disproved. There is always the possibility that a new observation or a new experiment will conflict with a long-standing theory.
II. Testing hypotheses

As just stated, experimental tests may lead either to the confirmation of the hypothesis, or to the ruling out of the hypothesis. The scientific method requires that an hypothesis be ruled out or modified if its predictions are clearly and repeatedly incompatible with experimental tests. Further, no matter how elegant a theory is, its predictions must agree with experimental results if we are to believe that it is a valid description of nature. In physics, as in every experimental science, "experiment is supreme" and experimental verification of hypothetical predictions is absolutely necessary. Experiments may test the theory directly (for example, the observation of a new particle) or may test for consequences derived from the theory using mathematics and logic (the rate of a radioactive decay process requiring the existence of the new particle). Note that the necessity of experiment also implies that a theory must be testable. Theories which cannot be tested, because, for instance, they have no observable ramifications (such as, a particle whose characteristics make it unobservable), do not qualify as scientific theories.

If the predictions of a long-standing theory are found to be in disagreement with new experimental results, the theory may be discarded as a description of reality, but it may continue to be applicable within a limited range of measurable parameters. For example, the laws of classical mechanics (Newton's Laws) are valid only when the velocities of interest are much smaller than the speed of light (that is, in algebraic form, when v/c << 1). Since this is the domain of a large portion of human experience, the laws of classical mechanics are widely, usefully and correctly applied in a large range of technological and scientific problems. Yet in nature we observe a domain in which v/c is not small. The motions of objects in this domain, as well as motion in the "classical" domain, are accurately described through the equations of Einstein's theory of relativity. We believe, due to experimental tests, that relativistic theory provides a more general, and therefore more accurate, description of the principles governing our universe, than the earlier "classical" theory. Further, we find that the relativistic equations reduce to the classical equations in the limit v/c << 1. Similarly, classical physics is valid only at distances much larger than atomic scales (x >> 10-8 m). A description which is valid at all length scales is given by the equations of quantum mechanics.

We are all familiar with theories which had to be discarded in the face of experimental evidence. In the field of astronomy, the earth-centered description of the planetary orbits was overthrown by the Copernican system, in which the sun was placed at the center of a series of concentric, circular planetary orbits. Later, this theory was modified, as measurements of the planets motions were found to be compatible with elliptical, not circular, orbits, and still later planetary motion was found to be derivable from Newton's laws.

Error in experiments have several sources. First, there is error intrinsic to instruments of measurement. Because this type of error has equal probability of producing a measurement higher or lower numerically than the "true" value, it is called random error. Second, there is non-random or systematic error, due to factors which bias the result in one direction. No measurement, and therefore no experiment, can be perfectly precise. At the same time, in science we have standard ways of estimating and in some cases reducing errors. Thus it is important to determine the accuracy of a particular measurement and, when stating quantitative results, to quote the measurement error. A measurement without a quoted error is meaningless. The comparison between experiment and theory is made within the context of experimental errors. Scientists ask, how many standard deviations are the results from the theoretical prediction? Have all sources of systematic and random errors been properly estimated? This is discussed in more detail in the appendix on Error Analysis and in Statistics Lab 1.
III. Common Mistakes in Applying the Scientific Method

As stated earlier, the scientific method attempts to minimize the influence of the scientist's bias on the outcome of an experiment. That is, when testing an hypothesis or a theory, the scientist may have a preference for one outcome or another, and it is important that this preference not bias the results or their interpretation. The most fundamental error is to mistake the hypothesis for an explanation of a phenomenon, without performing experimental tests. Sometimes "common sense" and "logic" tempt us into believing that no test is needed. There are numerous examples of this, dating from the Greek philosophers to the present day.

Another common mistake is to ignore or rule out data which do not support the hypothesis. Ideally, the experimenter is open to the possibility that the hypothesis is correct or incorrect. Sometimes, however, a scientist may have a strong belief that the hypothesis is true (or false), or feels internal or external pressure to get a specific result. In that case, there may be a psychological tendency to find "something wrong", such as systematic effects, with data which do not support the scientist's expectations, while data which do agree with those expectations may not be checked as carefully. The lesson is that all data must be handled in the same way.

Another common mistake arises from the failure to estimate quantitatively systematic errors (and all errors). There are many examples of discoveries which were missed by experimenters whose data contained a new phenomenon, but who explained it away as a systematic background. Conversely, there are many examples of alleged "new discoveries" which later proved to be due to systematic errors not accounted for by the "discoverers."

In a field where there is active experimentation and open communication among members of the scientific community, the biases of individuals or groups may cancel out, because experimental tests are repeated by different scientists who may have different biases. In addition, different types of experimental setups have different sources of systematic errors. Over a period spanning a variety of experimental tests (usually at least several years), a consensus develops in the community as to which experimental results have stood the test of time.
IV. Hypotheses, Models, Theories and Laws

In physics and other science disciplines, the words "hypothesis," "model," "theory" and "law" have different connotations in relation to the stage of acceptance or knowledge about a group of phenomena.

An hypothesis is a limited statement regarding cause and effect in specific situations; it also refers to our state of knowledge before experimental work has been performed and perhaps even before new phenomena have been predicted. To take an example from daily life, suppose you discover that your car will not start. You may say, "My car does not start because the battery is low." This is your first hypothesis. You may then check whether the lights were left on, or if the engine makes a particular sound when you turn the ignition key. You might actually check the voltage across the terminals of the battery. If you discover that the battery is not low, you might attempt another hypothesis ("The starter is broken"; "This is really not my car.")

The word model is reserved for situations when it is known that the hypothesis has at least limited validity. A often-cited example of this is the Bohr model of the atom, in which, in an analogy to the solar system, the electrons are described has moving in circular orbits around the nucleus. This is not an accurate depiction of what an atom "looks like," but the model succeeds in mathematically representing the energies (but not the correct angular momenta) of the quantum states of the electron in the simplest case, the hydrogen atom. Another example is Hook's Law (which should be called Hook's principle, or Hook's model), which states that the force exerted by a mass attached to a spring is proportional to the amount the spring is stretched. We know that this principle is only valid for small amounts of stretching. The "law" fails when the spring is stretched beyond its elastic limit (it can break). This principle, however, leads to the prediction of simple harmonic motion, and, as a model of the behavior of a spring, has been versatile in an extremely broad range of applications.

A scientific theory or law represents an hypothesis, or a group of related hypotheses, which has been confirmed through repeated experimental tests. Theories in physics are often formulated in terms of a few concepts and equations, which are identified with "laws of nature," suggesting their universal applicability. Accepted scientific theories and laws become part of our understanding of the universe and the basis for exploring less well-understood areas of knowledge. Theories are not easily discarded; new discoveries are first assumed to fit into the existing theoretical framework. It is only when, after repeated experimental tests, the new phenomenon cannot be accommodated that scientists seriously question the theory and attempt to modify it. The validity that we attach to scientific theories as representing realities of the physical world is to be contrasted with the facile invalidation implied by the expression, "It's only a theory." For example, it is unlikely that a person will step off a tall building on the assumption that they will not fall, because "Gravity is only a theory."

Changes in scientific thought and theories occur, of course, sometimes revolutionizing our view of the world (Kuhn, 1962). Again, the key force for change is the scientific method, and its emphasis on experiment.
V. Are there circumstances in which the Scientific Method is not applicable?

While the scientific method is necessary in developing scientific knowledge, it is also useful in everyday problem-solving. What do you do when your telephone doesn't work? Is the problem in the hand set, the cabling inside your house, the hookup outside, or in the workings of the phone company? The process you might go through to solve this problem could involve scientific thinking, and the results might contradict your initial expectations.

Like any good scientist, you may question the range of situations (outside of science) in which the scientific method may be applied. From what has been stated above, we determine that the scientific method works best in situations where one can isolate the phenomenon of interest, by eliminating or accounting for extraneous factors, and where one can repeatedly test the system under study after making limited, controlled changes in it.

There are, of course, circumstances when one cannot isolate the phenomena or when one cannot repeat the measurement over and over again. In such cases the results may depend in part on the history of a situation. This often occurs in social interactions between people. For example, when a lawyer makes arguments in front of a jury in court, she or he cannot try other approaches by repeating the trial over and over again in front of the same jury. In a new trial, the jury composition will be different. Even the same jury hearing a new set of arguments cannot be expected to forget what they heard before.
VI. Conclusion

The scientific method is intricately associated with science, the process of human inquiry that pervades the modern era on many levels. While the method appears simple and logical in description, there is perhaps no more complex question than that of knowing how we come to know things. In this introduction, we have emphasized that the scientific method distinguishes science from other forms of explanation because of its requirement of systematic experimentation. We have also tried to point out some of the criteria and practices developed by scientists to reduce the influence of individual or social bias on scientific findings. Further investigations of the scientific method and other aspects of scientific practice may be found in the references listed below.
VII. References

1. Wilson, E. Bright. An Introduction to Scientific Research (McGraw-Hill, 1952).

2. Kuhn, Thomas. The Structure of Scientific Revolutions (Univ. of Chicago Press, 1962).

3. Barrow, John. Theories of Everything (Oxford Univ. Press, 1991).