Ask a question, form a hypothesis, perform an experiment, collect data, and draw a conclusion, these are steps that are drilled into us from elementary school on how the scientific method works. This is an extremely linear and conclusive approach, which does not do justice to just how complex and iterative the scientific process truly is. Science is never concludes and certainly does not follow a predetermined list of steps. However there are certain things that go into every scientific investigation. Many times the scientific process begins with an idea. These ideas can come from concern over a practical problem, stem from a recent technological development, or just from simple curiosity. From these ideas, observations are made in the
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Hypotheses are a proposed explanation for a narrow set of phenomena and are usually based on experience, background knowledge, preliminary observations, or logic. Theories are explanations for a wide range of phenomena and can be so broad and powerful that they frame entire disciplines of study. They are often concise, coherent, systematic, and broadly applicable. It is important to remember that hypothesis and theories are not guesses, rather they are ideas and expectations built upon observations and data. At the heart of the scientific process lies testing. In this part of the process can make or break a scientist hypothesis or theory. Testing follows two steps. One, if the idea is correct, what would we expect to see, and two, does that expectation match what we actually observe. Based on how those two questions are answered, testing can either refute a hypothesis or it can lend support. Testing can be straightforward counting, rely on the development of tools, be time consuming, and take great effort. Some test may be completed in a second and some may continue for decades, there is no time …show more content…
From this data a lengthy review and analysis ensues. The data collected during testing may support one hypothesis and refute another. In some cases, once the data has been analyzed through statistical calculation, tabulation, and visual representation, it will reveal a faulty assumption, and the scientist will have to revise and redesign the test. But what happens when the data supports several hypotheses equally? This is where the iterative nature of the scientific process comes into play. There is no set limit on how many times you can test your hypothesis. Scientist can generate more specific expectations and test again and continue the process, discovering more information. These circumstances are often how knowledge is built and redefined, by testing new ideas and observations repeatedly. Also, in these circumstances the data is put against well-established theories to see if the new data is consistent. The old rule of K.I.S.S comes into play too; the simpler explanation is often preferred over the most complex one. Once the data is analyzed conclusions can be drawn. Peer review also comes into play. Scientist needs their work to be replicable in order to support their conclusions. If their experiments cannot be replicated, it suggests that the understanding and methods of testing were insufficient, and their conclusions will not be well
Hypotheses are a proposed explanation for a narrow set of phenomena and are usually based on experience, background knowledge, preliminary observations, or logic. Theories are explanations for a wide range of phenomena and can be so broad and powerful that they frame entire disciplines of study. They are often concise, coherent, systematic, and broadly applicable. It is important to remember that hypothesis and theories are not guesses, rather they are ideas and expectations built upon observations and data. At the heart of the scientific process lies testing. In this part of the process can make or break a scientist hypothesis or theory. Testing follows two steps. One, if the idea is correct, what would we expect to see, and two, does that expectation match what we actually observe. Based on how those two questions are answered, testing can either refute a hypothesis or it can lend support. Testing can be straightforward counting, rely on the development of tools, be time consuming, and take great effort. Some test may be completed in a second and some may continue for decades, there is no time …show more content…
From this data a lengthy review and analysis ensues. The data collected during testing may support one hypothesis and refute another. In some cases, once the data has been analyzed through statistical calculation, tabulation, and visual representation, it will reveal a faulty assumption, and the scientist will have to revise and redesign the test. But what happens when the data supports several hypotheses equally? This is where the iterative nature of the scientific process comes into play. There is no set limit on how many times you can test your hypothesis. Scientist can generate more specific expectations and test again and continue the process, discovering more information. These circumstances are often how knowledge is built and redefined, by testing new ideas and observations repeatedly. Also, in these circumstances the data is put against well-established theories to see if the new data is consistent. The old rule of K.I.S.S comes into play too; the simpler explanation is often preferred over the most complex one. Once the data is analyzed conclusions can be drawn. Peer review also comes into play. Scientist needs their work to be replicable in order to support their conclusions. If their experiments cannot be replicated, it suggests that the understanding and methods of testing were insufficient, and their conclusions will not be well