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☢️ Scientific Method

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◥ University. {q} PhD. {tr} Training. {R} Method. Fact. Etymology and usage The word fact derives from the Latin factum, and was first used in English with the same meaning: "a thing done or performed", a use that is now obsolete.[1] The common usage of "something that has really occurred or is the case" dates from the middle of the sixteenth century.[2] Fact is sometimes used synonymously with truth, as distinct from opinions, falsehoods, or matters of taste. This use is found in such phrases as, It is a fact that the cup is blue or Matter of fact,[3] and "... not history, nor fact, but imagination.

" Filmmaker Werner Herzog distinguishes clearly between the two, claiming that "fact creates norms, and truth illumination".[4] Fact also indicates a matter under discussion deemed to be true or correct, such as to emphasize a point or prove a disputed issue; (e.g., "... the fact of the matter is ... ").[5][6] Facts may be checked by reason, experiment, personal experience, or may be argued from authority.

Fact in philosophy Compound facts Fact in law. Scientific method. Diagram illustrating steps in the scientific method. The scientific method is an ongoing process, which usually begins with observations about the natural world. Human beings are naturally inquisitive, so they often come up with questions about things they see or hear and often develop ideas (hypotheses) about why things are the way they are. The best hypotheses lead to predictions that can be tested in various ways, including making further observations about nature. In general, the strongest tests of hypotheses come from carefully controlled and replicated experiments that gather empirical data. Although procedures vary from one field of inquiry to another, identifiable features are frequently shared in common between them.

Overview The DNA example below is a synopsis of this method Process Formulation of a question The question can refer to the explanation of a specific observation, as in "Why is the sky blue? " Hypothesis Prediction Testing Analysis DNA example Other components Replication 1. Steps of the Scientific Method. Please ensure you have JavaScript enabled in your browser. If you leave JavaScript disabled, you will only access a portion of the content we are providing. <a href="/science-fair-projects/javascript_help.php">Here's how. </a> What is the Scientific Method? The scientific method is a process for experimentation that is used to explore observations and answer questions. Does this mean all scientists follow exactly this process? No. 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.

Whether you are doing a science fair project, a classroom science activity, independent research, or any other hands-on science inquiry understanding the steps of the scientific method will help you focus your scientific question and work through your observations and data to answer the question as well as possible. Educator Tools for Teaching the Scientific Method. Variable. From Wikipedia, the free encyclopedia Variable may refer to: Dependent and independent variables. Variables used in an experiment or modelling can be divided into three types: "dependent variable", "independent variable", or other. The "dependent variable" represents the output or effect, or is tested to see if it is the effect.

The "independent variables" represent the inputs or causes, or are tested to see if they are the cause. Other variables may also be observed for various reasons. Use Calculus gives a relation between y and x. Statistics In a statistics experiment, the dependent variable is the event studied and expected to change whenever the independent variable is altered.[1] Data mining In data mining tools (for multivariate statistics and machine learning), the depending variable is assigned a role as target variable (or in some tools as label attribute), while a dependent variable may be assigned a role as regular variable.[2] Known values for the target variable are provided for the training data set and test data set, but should be predicted for other data.

Modelling. Control variable. The term control variable has different meanings, depending on the area/place in which it is used. The control variable is something that is constant and unchanged in an experiment. Further, a control variable strongly influences values; it is held constant to test the relative impact of independent variables. Experimental examples[edit] In scientific experimentation, a control variable is the one element that must not be changed throughout an experiment because it also affects the other independent variables being tested, thus affecting the outcome of the experiment. Other candidates for controlled variables might be, for example, if you are testing a product's effects on two plants, the soil type and the pot shape may be two controlled variables. In control theory[edit] In control theory, controlled variables are the variables that are input into the control system.

In computer programming[edit] Examples[edit] See also[edit] Multivariable calculus (multiple variables) Typical operations[edit] Limits and continuity[edit] A study of limits and continuity in multivariable calculus yields many counter-intuitive results not demonstrated by single-variable functions. For example, there are scalar functions of two variables with points in their domain which give a particular limit when approached along any arbitrary line, yet give a different limit when approached along a parabola.

For example, the function approaches zero along any line through the origin. However, when the origin is approached along a parabola , it has a limit of 0.5. Continuity in each argument is not sufficient for multivariate continuity: For instance, in the case of a real-valued function with two real-valued parameters, , continuity of in for fixed and continuity of does not imply continuity of . It is easy to check that all real-valued functions (with one real-valued argument) that are given by are continuous in (for any fixed ). Are continuous as is symmetric with regards to and .

(for natural if. Mechanism. From Wikipedia, the free encyclopedia Mechanism may refer to: Level of measurement. In statistics and quantitative research methodology, various attempts have been made to classify variables (or types of data) and thereby develop a taxonomy of levels of measurement or scales of measure. Perhaps the best known are those developed by the psychologist Stanley Smith Stevens. He proposed four types: nominal, ordinal, interval, and ratio. Typology[edit] Nominal scale[edit] The nominal type, sometimes also called the qualitative type, differentiates between items or subjects based only on their names or (meta-)categories and other qualitative classifications they belong to; thus dichotomous data involves the construction of classifications as well as the classification of items.

Central tendency[edit] Ordinal scale[edit] The ordinal type allows for rank order (1st, 2nd, 3rd, etc.) by which data can be sorted, but still does not allow for relative degree of difference between them. Central tendency[edit] Interval scale[edit] Central tendency and statistical dispersion[edit] L. Theory. Thomas Kuhn. Thomas Samuel Kuhn (/ˈkuːn/; July 18, 1922 – June 17, 1996) was an American physicist, historian, and philosopher of science whose controversial 1962 book The Structure of Scientific Revolutions was deeply influential in both academic and popular circles, introducing the term "paradigm shift", which has since become an English-language staple. Life[edit] Kuhn was born in Cincinnati, Ohio, to Samuel L.

Kuhn, an industrial engineer, and Minette Stroock Kuhn. He graduated from The Taft School in Watertown, CT, in 1940, where he became aware of his serious interest in mathematics and physics. He obtained his B.S. degree in physics from Harvard University in 1943, where he also obtained M.S. and Ph.D. degrees in physics in 1946 and 1949, respectively.

Thomas Kuhn was married twice, first to Kathryn Muhs with whom he had three children, then to Jehane Barton Burns (Jehane R. Kuhn was an agnostic.[4] His family was Jewish on both sides. The Structure of Scientific Revolutions[edit] Honors[edit] Hypothesis. A hypothesis (plural hypotheses) is a proposed explanation for a phenomenon. For a hypothesis to be a scientific hypothesis, the scientific method requires that one can test it. Scientists generally base scientific hypotheses on previous observations that cannot satisfactorily be explained with the available scientific theories. Even though the words "hypothesis" and "theory" are often used synonymously, a scientific hypothesis is not the same as a scientific theory.

A working hypothesis is a provisionally accepted hypothesis proposed for further research.[1] The adjective hypothetical, meaning "having the nature of a hypothesis", or "being assumed to exist as an immediate consequence of a hypothesis", can refer to any of these meanings of the term "hypothesis". Uses[edit] In Plato's Meno (86e–87b), Socrates dissects virtue with a method used by mathematicians,[2] that of "investigating from a hypothesis Scientific hypothesis[edit] Working hypothesis[edit] See also[edit] Notes[edit]

Occam's razor. The sun, moon and other solar system planets can be described as revolving around the Earth. However that explanation's ideological and complex assumptions are completely unfounded compared to the modern consensus that all solar system planets revolve around the Sun. Ockham's razor (also written as Occam's razor and in Latin lex parsimoniae) is a principle of parsimony, economy, or succinctness used in problem-solving devised by William of Ockham (c. 1287 - 1347). It states that among competing hypotheses, the one with the fewest assumptions should be selected. Other, more complicated solutions may ultimately prove correct, but—in the absence of certainty—the fewer assumptions that are made, the better. Solomonoff's theory of inductive inference is a mathematically formalized Occam's Razor:[2][3][4][5][6][7] shorter computable theories have more weight when calculating the probability of the next observation, using all computable theories which perfectly describe previous observations.

Theory choice. A main problem in the philosophy of science in the early 20th century, and under the impact of the new and controversial theories of relativity and quantum physics, came to involve how scientists should choose between competing theories. The classical answer would be to select the theory which was best verified, against which Karl Popper argued that competing theories should be subjected to comparative tests and the one chosen which survived the tests. If two theories could not, for practical reasons, be tested one should prefer the one with the highest degree of empirical content, said Popper in The Logic of Scientific Discovery. Mathematician and physicist Henri Poincaré instead, like many others, proposed simplicity as a criterion.[1] One should choose the mathematically simplest or most elegant approach. Popper's solution was subsequently criticized by Thomas S. Kuhn in The Structure of Scientific Revolutions. Explanatory power. Explanatory power is the ability of a hypothesis to effectively explain the subject matter it pertains to.

One theory is sometimes said to have more explanatory power than another theory about the same subject matter if it offers greater predictive power. That is, if it offers more details about what we should expect to see, and what we should not. Explanatory power may also suggest that more details of causal relations are provided, or that more facts are accounted for. Scientist David Deutsch adds that a good theory is not just predictive and falsifiable (i.e. testable); a good explanation also provides specific details which fit together so tightly that it is difficult to change one detail without affecting the whole theory. The opposite of explanatory power is explanatory impotence. Overview[edit] Deutsch says that the truth consists of detailed and "hard to vary assertions about reality" Deutsch takes examples from Greek mythology. References[edit]

Experiment. Even very young children perform rudimentary experiments in order to learn about the world. An experiment is an orderly procedure carried out with the goal of verifying, refuting, or establishing the validity of a hypothesis. Controlled experiments provide insight into cause-and-effect by demonstrating what outcome occurs when a particular factor is manipulated. Controlled experiments vary greatly in their goal and scale, but always rely on repeatable procedure and logical analysis of the results. There also exist natural experimental studies. A child may carry out basic experiments to understand the nature of gravity, while teams of scientists may take years of systematic investigation to advance the understanding of a phenomenon.

Overview[edit] In the scientific method, an experiment is an empirical method that arbitrates between competing models or hypotheses.[1][2] Experimentation is also used to test existing theories or new hypotheses in order to support them or disprove them.[3][4] Knowledge management experiment. Computer science experiment. Cross-validation (statistics) Reproducibility. Cognitive map. What is hypothesis and give me some examples? Hypothetico-deductive model. Karl Popper.

Complexity. Stroop effect. Benchmarking. Competition. Algorithm. Text mining.