Pole shift hypothesis

Polar Shift" redirects here. For the Clive Cussler novel, see Polar Shift (novel). For the Antarctica benefit compilation, see Polar Shift (album).

This article is about the hypothesis of pole shift in its historical context. For a description of the modern scientific understanding, see true polar wander.

The cataclysmic pole shift hypothesis suggests that there have been geologically rapid shifts in the relative positions of the modern-day geographic locations of the poles and the axis of rotation of the Earth, creating calamities such as floods and tectonic events.^[1]
There is evidence of precession and changes in axial tilt, but this change is on much longer time-scales and does not involve relative motion of the spin axis with respect to the planet. However, in what is known as true polar wander, the solid Earth can rotate with respect to a fixed spin axis. Research shows that during the last 200,000,000 years a total true polar wander of some 30° has occurred, but that no super-rapid shifts in the Earth's pole were found during this period.^[2] A characteristic rate of true polar wander is 1° per million years or less.^[3] Between approximately 790 and 810 million years ago, when the supercontinent Rodinia existed, two geologically-rapid phases of true polar wander may have occurred. In each of these, the magnetic poles of the Earth shifted by ~155°.^[4]

Definition and clarification

The geographic poles of the Earth are the points on the surface of the planet that are intersected by the axis of rotation. The pole shift hypothesis describes a change in location of these poles with respect to the underlying surface – a phenomenon distinct from the changes in axial orientation with respect to the plane of the ecliptic that are caused by precession and nutation, and from true polar wander.
Pole shift hypotheses are not connected with plate tectonics, the well-accepted geological theory that the Earth's surface consists of solid plates which shift over a fluid asthenosphere; nor with continental drift, the corollary to plate tectonics which maintains that locations of the continents have moved slowly over the face of the Earth,^[5] resulting in the gradual emerging and breakup of continents and oceans over hundreds of millions of years.^[6]
Pole shift hypotheses are not the same as geomagnetic reversal, the periodic reversal of the Earth's magnetic field (effectively switching the north and south magnetic poles).

Speculative history

In popular literature, many conjectures have been suggested involving very rapid polar shift. A slow shift in the poles would display the most minor alterations and no destruction. A more dramatic view assumes more rapid changes, with dramatic alterations of geography and localized areas of destruction due to earthquakes and tsunamis.

Early proponents

An early mention of a shifting of the Earth's axis can be found in an 1872 article entitled "Chronologie historique des Mexicains"^[7] by Charles Étienne Brasseur de Bourbourg, a specialist in Mesoamerican codices who interpreted ancient Mexican myths as evidence for four periods of global cataclysms that had begun around 10,500 BCE. In 1948, Hugh Auchincloss Brown, an electrical engineer, advanced a hypothesis of catastrophic pole shift. Brown also argued that accumulation of ice at the poles caused recurring tipping of the axis, identifying cycles of approximately seven millennia.^[8][9]
In his controversial 1950 work Worlds in Collision, Immanuel Velikovsky postulated that the planet Venus emerged from Jupiter as a comet. During two proposed near approaches in about 1,450 BCE, he suggested that the direction of the Earth's rotation was changed radically, then reverted to its original direction on the next pass. This disruption supposedly caused earthquakes, tsunamis, and the parting of the Red Sea. Further, he said near misses by Mars between 776 and 687 BCE also caused the Earth's axis to change back and forth by ten degrees. Velikovsky supported his work with historical records, although his studies were mainly ridiculed by the scientific community.^[10]
Charles Hapgood is now perhaps the best remembered early proponent. In his books The Earth's Shifting Crust (1958) (which includes a foreword by Albert Einstein that was written before the theory of plate tectonics was developed)^[11] and Path of the Pole (1970). Hapgood, building on Adhemar's much earlier model,^{[citation needed]} speculated that the ice mass at one or both poles over-accumulates and destabilizes the Earth's rotational balance, causing slippage of all or much of Earth's outer crust around the Earth's core, which retains its axial orientation.
Based on his own research, Hapgood argued that each shift took approximately 5,000 years, followed by 20,000- to 30,000-year periods with no polar movements. Also, in his calculations, the area of movement never covered more than 40 degrees. Hapgood's examples of recent locations for the North Pole include Hudson Bay (60˚N, 73˚W), the Atlantic Ocean between Iceland and Norway (72˚N, 10˚E) and Yukon (63˚N, 135˚W).
However, in his subsequent work The Path of the Pole, Hapgood conceded Einstein's point that the weight of the polar ice would be insufficient to bring about a polar shift. Instead, Hapgood argued that the forces that caused the shifts in the crust must be located below the surface. He had no satisfactory explanation for how this could occur.^[12]
In 1974 Flavio Barbiero, an engineer and explorer, theorized that shifting of the Earth's axis took place 11,000 years ago and caused what has been subsequently recorded by myths as the destruction of Atlantis and Mu. That shifting was likely caused by the impact of a comet on the Earth surface and the current position of Atlantis has to be sought under the Antarctic ice sheet.^[13]
Hapgood wrote to a Canadian librarian, Rand Flem-Ath, encouraging him in his pursuit of scientific evidence to back Hapgood's claims and in his expansion of the hypothesis. Flem-Ath published the results of this work in 1995 in When the Sky Fell co-written with his wife.^[14]

Recent conjectures

The field has attracted a number of authors offering a variety of evidence.
In the 1970s and 1980s a series of books not intended as fiction by former Washington newspaper reporter Ruth Shick Montgomery elaborates on Edgar Cayce readings.^[15]
In 1997 Richard W. Noone published 5/5/2000, ICE: The Ultimate Disaster. This book argued that a cataclysmic shift of the Earth's ice cap covering Antarctica caused by a planetary alignment and solar storms, would lead to crustal displacement on May 5, 2000.^[16]
In 1998 retired civil engineer James G. Bowles proposed in Atlantis Rising magazine a mechanism by which a polar shift could occur. He named this Rotational-Bending, or the RB-effect. He hypothesized that combined gravitational effects of the Sun and the Moon pulled at the Earth's crust at an oblique angle. This force steadily wore away at the underpinnings that linked the crust to the inner mantle. This generates a plastic zone that allows the crust to rotate with respect to the lower layers. Centrifugal forces will act on the mass of ice at the poles, causing them to move to the equator.^[17]
Books on this subject have been published by William Hutton, including the 1996 book Coming Earth Changes: Causes and Consequences of the Approaching Pole Shift (ISBN 0876043619), which compared geologic records with the psychic readings of Edgar Cayce and predicted catastrophic climate changes before the end of 2001. In 2004 Hutton and co-author Jonathan Eagle published Earth's Catastrophic Past and Future: A Scientific Analysis of Information Channeled by Edgar Cayce (ISBN 1-58112-517-8), which summarizes possible mechanisms and the timing of a future pole shift.

Scientific research

It is now established that true polar wander has occurred at various times in the past, but at rates of 1° per million years or less.^[2][3][18] Analysis of the evidence does not lend credence to Hapgood's hypothesized rapid displacement of layers of the Earth.^[19] Although Hapgood drastically overestimated the effects of changing mass distributions across the Earth,^{[citation needed]} calculations show that changing mass distributions both on the surface and in the mantle can cause true polar wander.

True polar wander

Main article: True polar wander

True polar wander, or the motion of the solid Earth with respect to a fixed spin axis that causes the spin axis to lie over a new geographic position, does occur. This is because of changes in mass distribution throughout the Earth that modify its moment of inertia tensor. The Earth consistently readjusts its orientation with respect to its spin axis such that its spin axis is parallel to the axis about which it has its greatest moment of inertia.^[4] This readjustment is very slow. In 2001, historical evidence for true polar wander was found in paleomagnetic data from granitic rocks from across North America. The data from these rocks conflict with the hypothesis of a cataclysmic true polar wander event. This evidence indicated that the geographical poles have not deviated by more than about 5° over the last 130 million years.^[20] More rapid past possible occurrences of true polar wander have been measured: from 790 to 810 million years ago, true polar wander of approximately 55° may have occurred twice.^[4]

Ecosystem

n ecosystem is a community of living organisms (plants, animals and microbes) in conjunction with the nonliving components of their environment (things like air, water and mineral soil), interacting as a system.^[2] These components are regarded as linked together through nutrient cycles and energy flows.^[3] As ecosystems are defined by the network of interactions among organisms, and between organisms and their environment,^[4] they can come in any size but usually encompass specific, limited spaces^[5] (although some scientists say that the entire planet is an ecosystem).^[6] Energy, water, nitrogen and soil minerals are other essential abiotic components of an ecosystem. The energy that flows through ecosystems is obtained primarily from the sun. It generally enters the system through photosynthesis, a process that also captures carbon from the atmosphere. By feeding on plants and on one another, animals play an important role in the movement of matter and energy through the system. They also influence the quantity of plant and microbial biomass present. By breaking down dead organic matter, decomposers release carbon back to the atmosphere and facilitate nutrient cycling by converting nutrients stored in dead biomass back to a form that can be readily used by plants and other microbes.^[7]
Ecosystems are controlled both by external and internal factors. External factors such as climate, the parent material which forms the soil and topography, control the overall structure of an ecosystem and the way things work within it, but are not themselves influenced by the ecosystem.^[8] Other external factors include time and potential biota. Ecosystems are dynamic entities—invariably, they are subject to periodic disturbances and are in the process of recovering from some past disturbance.^[9] Ecosystems in similar environments that are located in different parts of the world can end up doing things very differently simply because they have different pools of species present.^[8] The introduction of non-native species can cause substantial shifts in ecosystem function. Internal factors not only control ecosystem processes but are also controlled by them and are often subject to feedback loops.^[8] While the resource inputs are generally controlled by external processes like climate and parent material, the availability of these resources within the ecosystem is controlled by internal factors like decomposition, root competition or shading.^[8] Other internal factors include disturbance, succession and the types of species present. Although humans exist and operate within ecosystems, their cumulative effects are large enough to influence external factors like climate.^[8]
Biodiversity affects ecosystem function, as do the processes of disturbance and succession. Ecosystems provide a variety of goods and services upon which people depend; the principles of ecosystem management suggest that rather than managing individual species, natural resources should be managed at the level of the ecosystem itself. Classifying ecosystems into ecologically homogeneous units is an important step towards effective ecosystem management, but there is no single, agreed-upon way to do this.

Graphics

Graphics (from Greek γραφικός graphikos) are visual presentations on some surface, such as a wall, canvas, screen, paper, or stone to brand, inform, illustrate, or entertain. Graphics word is derived from the word graph. A graph has x and y axis. Same way something which is created in digital word is seen on a digital screen, this screen also has x and y axis. So the output on any digital device is termed as graphics. In other words an image that is generated by a computer called graphics. The pictorial representation and manipulation of data, as used in computer-aided design and manufacture, in typesetting and the graphic arts, and in educational and recreational programs.
Examples are photographs, drawings, Line Art, graphs, diagrams, typography, numbers, symbols, geometric designs, maps, engineering drawings, or other images. Graphics often combine text, illustration, and color. Graphic design may consist of the deliberate selection, creation, or arrangement of typography alone, as in a brochure, flier, poster, web site, or book without any other element. Clarity or effective communication may be the objective, association with other cultural elements may be sought, or merely, the creation of a distinctive style.
Graphics can be functional or artistic. The latter can be a recorded version, such as a photograph, or an interpretation by a scientist to highlight essential features, or an artist, in which case the distinction with imaginary graphics may become blurred.

History

Main article: History of graphic design

The earliest graphics known to anthropologists studying prehistoric periods are cave paintings and markings on boulders, bone, ivory, and antlers, which were created during the Upper Palaeolithic period from 40,000–10,000 B.C. or earlier. Many of these were found to record astronomical, seasonal, and chronological details. Some of the earliest graphics and drawings known to the modern world, from almost 6,000 years ago, are that of engraved stone tablets and ceramic cylinder seals, marking the beginning of the historic periods and the keeping of records for accounting and inventory purposes. Records from Egypt predate these and papyrus was used by the Egyptians as a material on which to plan the building of pyramids; they also used slabs of limestone and wood. From 600–250 BC, the Greeks played a major role in geometry. They used graphics to represent their mathematical theories such as the Circle Theorem and the Pythagorean theorem.
In art, "graphics" is often used to distinguish work in a monotone and made up of lines, as opposed to painting.

Drawing

Main articles: Drawing and Technical drawing

Drawing generally involves making marks on a surface by applying pressure from a tool, or moving a tool across a surface. Common tools are graphite pencils, pen and ink, inked brushes, wax color pencils, crayons, charcoals, pastels, and markers. Digital tools which simulate the effects of these are also used. The main techniques used in drawing are line drawing, hatching, crosshatching, random hatching, scribbling, stippling, blending, and shading.
Drawing is generally considered distinct from painting, in which colored pigments are suspended in a liquid medium and are usually applied with a brush. Notable great drawers include Michelangelo, Rembrandt, Raphael and Leonardo da Vinci.
Many people choose drawing as a main art style, or they may use it to make sketches for paintings, sculptures and other types of art. The other term is Engineering Graphics, preferably the language of engineers that simulates Three Dimensional capability of engineer to plan and Implement his ideas. It comprises Projection, Development, Perspective, Section, Intersection, and Isometric ideations.

Printmaking

Main article: Printmaking

Woodblock printing, including images is first seen in China after paper was invented (about A.D. 105). In the West the main techniques have been woodcut, engraving and etching, but there are many others.

Etching

Main article: Etching

Etching is an intaglio method of printmaking in which the image is incised into the surface of a metal plate using an acid. The acid eats the metal, leaving behind roughened areas, or, if the surface exposed to the acid is very thin, burning a line into the plate. The use of the process in printmaking is believed to have been invented by Daniel Hopfer (c. 1470–1536) of Augsburg, Germany, who decorated armour in this way.
Etching is also used in the manufacturing of printed circuit boards and semiconductor devices.

Line Art

Main article: Line art

Line art is a rather non-specific term sometimes used for any image that consists of distinct straight and curved lines placed against a (usually plain) background, without gradations in shade (darkness) or hue (color) to represent two-dimensional or three-dimensional objects. Line art is usually monochromatic, although lines may be of different colors.

Illustration

Main article: Illustration

An illustration of a character from a story; also, an illustration of illustrations

An illustration is a visual representation such as a drawing, painting, photograph or other work of art that stresses subject more than form. The aim of an illustration is to elucidate or decorate a story, poem or piece of textual information (such as a newspaper article), traditionally by providing a visual representation of something described in the text. The editorial cartoon, also known as a political cartoon, is an illustration containing a political or social message.
Illustrations can be used to display a wide range of subject matter and serve a variety of functions, such as:

• giving faces to characters in a story
• displaying a number of examples of an item described in an academic textbook (e.g. A Typology)
• visualising step-wise sets of instructions in a technical manual
• communicating subtle thematic tone in a narrative
• linking brands to the ideas of human expression, individuality and creativity
• making a reader laugh or smile
• for fun (to make laugh) funny

Graphs

A graph or chart is a type of information graphic that represents tabular, numeric data. Charts are often used to make it easier to understand large quantities of data and the relationships between different parts of the data.

Diagrams

Main article: Diagrams

A diagram is a simplified and structured visual representation of concepts, ideas, constructions, relations, statistical data, etc., used to visualize and clarify the topic.

Symbols

Main article: Symbols

A symbol, in its basic sense, is a representation of a concept or quantity; i.e., an idea, object, concept, quality, etc. In more psychological and philosophical terms, all concepts are symbolic in nature, and representations for these concepts are simply token artifacts that are allegorical to (but do not directly codify) a symbolic meaning, or symbolism.

Graphic Design

Such things as working with Photoshop or some other computer based program to produce designs such as Album Cover, Web Page layouts, or just wallpaper you want to use for your computer. This area of Computer making Graphic Designing is becoming really popular and jobs are looking for people that are good in this area.

Maps

Main article: Maps

A map is a simplified depiction of a space, a navigational aid which highlights relations between objects within that space. Usually, a map is a two-dimensional, geometrically accurate representation of a three-dimensional space.
One of the first 'modern' maps was made by Waldseemüller.

Photography

Main article: Photography

One difference between photography and other forms of graphics is that a photographer, in principle, just records a single moment in reality, with seemingly no interpretation. However, a photographer can choose the field of view and angle, and may also use other techniques, such as various lenses to distort the view or filters to change the colors. In recent times, digital photography has opened the way to an infinite number of fast, but strong, manipulations. Even in the early days of photography, there was controversy over photographs of enacted scenes that were presented as 'real life' (especially in war photography, where it can be very difficult to record the original events). Shifting the viewer's eyes ever so slightly with simple pinpricks in the negative could have a dramatic effect.
The choice of the field of view can have a strong effect, effectively 'censoring out' other parts of the scene, accomplished by cropping them out or simply not including them in the photograph. This even touches on the philosophical question of what reality is. The human brain processes information based on previous experience, making us see what we want to see or what we were taught to see. Photography does the same, although the photographer interprets the scene for their viewer.

Engineering drawings

Image of a part represented in First Angle Projection

Main article: Engineering drawings

An engineering drawing is a type of drawing and is technical in nature, used to fully and clearly define requirements for engineered items. It is usually created in accordance with standardized conventions for layout, nomenclature, interpretation, appearance (such as typefaces and line styles), size, etc.

Computer graphics

Main article: Computer graphics

There are two types of computer graphics: raster graphics, where each pixel is separately defined (as in a digital photograph), and vector graphics, where mathematical formulas are used to draw lines and shapes, which are then interpreted at the viewer's end to produce the graphic. Using vectors results in infinitely sharp graphics and often smaller files, but, when complex,like vectors take time to render and may have larger file sizes than a raster equivalent.
In 1950, the first computer-driven display was attached to MIT's Whirlwind I computer to generate simple pictures. This was followed by MIT's TX-0 and TX-2, interactive computing which increased interest in computer graphics during the late 1950s. In 1962, Ivan Sutherland invented Sketchpad, an innovative program that influenced alternative forms of interaction with computers.
In the mid-1960s, large computer graphics research projects were begun at MIT, General Motors, Bell Labs, and Lockheed Corporation. Douglas T. Ross of MIT developed an advanced compiler language for graphics programming. S.A.Coons, also at MIT, and J. C. Ferguson at Boeing, began work in sculptured surfaces. GM developed their DAC-1 system, and other companies, such as Douglas, Lockheed, and McDonnell, also made significant developments. In 1968, ray tracing was first described by Arthur Appel of the IBM Research Center, Yorktown Heights, N.Y.^[1]
During the late 1970s, personal computers became more powerful, capable of drawing both basic and complex shapes and designs. In the 1980s, artists and graphic designers began to see the personal computer, particularly the Commodore Amiga and Macintosh, as a serious design tool, one that could save time and draw more accurately than other methods. 3D computer graphics became possible in the late 1980s with the powerful SGI computers, which were later used to create some of the first fully computer-generated short films at Pixar. The Macintosh remains one of the most popular tools for computer graphics in graphic design studios and businesses.
Modern computer systems, dating from the 1980s and onwards, often use a graphical user interface (GUI) to present data and information with symbols, icons and pictures, rather than text. Graphics are one of the five key elements of multimedia technology.
3D graphics became more popular in the 1990s in gaming, multimedia and animation. In 1996, Quake, one of the first fully 3D games, was released. In 1995, Toy Story, the first full-length computer-generated animation film, was released in cinemas. Since then, computer graphics have become more accurate and detailed, due to more advanced computers and better 3D modeling software applications, such as Maya, 3D Studio Max, and Cinema 4D.
Another use of computer graphics is screensavers, originally intended to preventing the layout of much-used GUIs from 'burning into' the computer screen. They have since evolved into true pieces of art, their practical purpose obsolete; modern screens are not susceptible to such burn in artifacts.

Web graphics

Signature art used on web forums

In the 1990s, Internet speeds increased, and Internet browsers capable of viewing images were released, the first being Mosaic. Websites began to use the GIF format to display small graphics, such as banners, advertisements and navigation buttons, on web pages. Modern web browsers can now display JPEG, PNG and increasingly, SVG images in addition to GIFs on web pages. SVG, and to some extent VML, support in some modern web browsers have made it possible to display vector graphics that are clear at any size. Plugins expand the web browser functions to display animated, interactive and 3-D graphics contained within file formats such as SWF and X3D.
Modern web graphics can be made with software such as Adobe Photoshop, the GIMP, or Corel Paint Shop Pro. Users of Microsoft Windows have MS Paint, which many find to be lacking in features. This is because MS Paint is a drawing package and not a graphics package.
Numerous platforms and websites have been created to cater to web graphics artists and to host their communities. A growing number of people use create internet forum signatures—generally appearing after a user's post—and other digital artwork, such as photo manipulations and large graphics. With computer games' developers creating their own communities around their products, many more websites are being developed to offer graphics for the fans and to enable them to show their appreciation of such games in their own gaming profiles.

Uses

Graphics are visual elements often used to point readers and viewers to particular information. They are also used to supplement text in an effort to aid readers in their understanding of a particular concept or make the concept more clear or interesting. Popular magazines, such as TIME, Wired and Newsweek, usually contain graphic material in abundance to attract readers, unlike the majority of scholarly journals. In computing, they are used to create a graphical interface for the user; and graphics are one of the five key elements of multimedia technology. Graphics are among the primary ways of advertising the sale of goods or services.

Business

Graphics are commonly used in business and economics to create financial charts and tables. The term Business Graphics came into use in the late 1970s, when personal computers became capable of drawing graphs and charts instead of using a tabular format. Business Graphics can be used to highlight changes over a period of time.

Advertising

Advertising is one of the most profitable uses of graphics; artists often do advertising work or take advertising potential into account when creating art, to increase the chances of selling the artwork.

Political

The use of graphics for overtly political purposes—cartoons, graffiti, poster art, flag design, etc.—is a centuries old practice which thrives today in every part of the world. The Northern Irish murals are one such example.

Education

Graphics are heavily used in textbooks, especially those concerning subjects such as geography, science, and mathematics, in order to illustrate theories and concepts, such as the human anatomy. Diagrams are also used to label photographs and pictures.
Educational animation is an important emerging field of graphics. Animated graphics have obvious advantages over static graphics when explaining subject matter that changes over time.
The Oxford Illustrated Dictionary uses graphics and technical illustrations to make reading material more interesting and easier to understand. In an encyclopedia, graphics are used to illustrate concepts and show examples of the particular topic being discussed.
In order for a graphic to function effectively as an educational aid, the learner must be able to interpret it successfully. This interpretative capacity is one aspect of graphicacy.

Film and animation

Computer graphics are often used in the majority of new feature films, especially those with a large budget. Films that heavily use computer graphics include The Lord of the Rings film trilogy, the Harry Potter films, Spider-Man and War of the Worlds.

Graphics education

The majority of schools, colleges and universities around the world educate students on the subject of graphics and art.
The subject is taught in a broad variety of ways, each course teaching its own distinctive balance of craft skills and intellectual response to the client's needs.
Some graphics courses prioritize traditional craft skills—drawing, printmaking and typography—over modern craft skills. Other courses may place an emphasis on teaching digital craft skills. Still other courses may downplay the crafts entirely, concentrating on training students to generate novel intellectual responses that engage with the brief. Despite these apparent differences in training and curriculum, the staff and students on any of these courses will generally consider themselves to be graphic designers.
The typical pedagogy of a graphic design (or graphic communication, visual communication, graphic arts or any number of synonymous course titles) will be broadly based on the teaching models developed in the Bauhaus school in Germany or Vkhutemas in Russia. The teaching model will tend to expose students to a variety of craft skills (currently everything from drawing to motion capture), combined with an effort to engage the student with the world of visual culture.

Famous graphic designers

Aldus Manutius designed the first Italic type style which is often used in desktop publishing and graphic design. April Greiman is known for her influential poster design. Paul Rand is well known as a design pioneer for designing many popular corporate logos, including the logo for IBM, NeXT and UPS. William Caslon, during the mid-18th century, designed many typefaces, including ITC Founder's Caslon, ITC Founder's Caslon Ornaments, Caslon Graphique, ITC Caslon No. 224, Caslon Old Face and Big Caslon.

Examples of graphics

• 

  Photograph
  
• 

  Drawing
  

Statistics

Scope

Some consider statistics to be a mathematical body of science pertaining to the collection, analysis, interpretation or explanation, and presentation of data,^[5] while others consider it a branch of mathematics^[6] concerned with collecting and interpreting data. Because of its empirical roots and its focus on applications, statistics is usually considered to be a distinct mathematical science rather than a branch of mathematics.^[7][8] Much of statistics is non-mathematical: ensuring that data collection is undertaken in a way that allows valid conclusions to be drawn; coding and archiving of data so that information is retained and made useful for international comparisons of official statistics; reporting of results and summarised data (tables and graphs) in ways that are comprehensible to those who need to make use of them; implementing procedures that ensure the privacy of census information.
Statisticians improve the quality of data by coming up with a specific design of experiments and survey sampling. Statistics itself also provides tools for prediction and forecasting the use of data and statistical models. Statistics is applicable to a wide variety of academic disciplines, including natural and social sciences, government, and business. Statistical consultants are available to provide help for organizations and companies without direct access to expertise relevant to their particular questions.
Statistical methods can be used for summarizing or describing a collection of data; this is called descriptive statistics. This is particularly useful in research, when communicating the results of experiments. In addition, patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations, and are then used for drawing inferences about the process or population being studied; this is called inferential statistics. Inference is a vital element of scientific advance, since it provides a means for drawing conclusions from data that are subject to random variation. To prove the propositions being investigated further, the conclusions are tested as well, as part of the scientific method. Descriptive statistics and analysis of the new data tend to provide more information as to the truth of the proposition.
Descriptive statistics and the application of inferential statistics (a.k.a., predictive statistics) together comprise applied statistics.^{[9][verification needed]} Theoretical statistics concerns both the logical arguments underlying justification of approaches to statistical inference, as well encompassing mathematical statistics. Mathematical statistics includes not only the manipulation of probability distributions necessary for deriving results related to methods of estimation and inference, but also various aspects of computational statistics and the design of experiments.
Statistics is closely related to the probability theory, with which it is often grouped; the difference is roughly that in probability theory, one starts from the given parameters of a total population to deduce probabilities pertaining to samples, but statistical inference moves in the opposite direction, inductive inference from samples to the parameters of a larger or total population.

History

Main articles: History of statistics and Founders of statistics

The use of statistical methods dates back at least to the 5th century BC. The earliest writing on statistics was found in a 9th century book entitled: "Manuscript on Deciphering Cryptographic Messages", written by Al-Kindi. In his book, he gave a detailed description of how to use statistics and frequency analysis to decipher encrypted messages, this was the birth of both statistics and cryptanalysis, according to the Saudi engineer Ibrahim Al-Kadi.^[10][11]
The Nuova Cronica, a 14th century history of Florence by the Florentine banker and official Giovanni Villani, includes much statistical information on population, ordinances, commerce and trade, education, and religious facilities and has been described as the first introduction of statistics as a positive element in history.^[12]
Some scholars pinpoint the origin of statistics to 1663, with the publication of Natural and Political Observations upon the Bills of Mortality by John Graunt.^[13] Early applications of statistical thinking revolved around the needs of states to base policy on demographic and economic data, hence its stat- etymology. The scope of the discipline of statistics broadened in the early 19th century to include the collection and analysis of data in general. Today, statistics is widely employed in government, business, and natural and social sciences.
Its mathematical foundations were laid in the 17th century with the development of the probability theory by Blaise Pascal and Pierre de Fermat. Probability theory arose from the study of games of chance. The method of least squares was first described by Carl Friedrich Gauss around 1794. The use of modern computers has expedited large-scale statistical computation, and has also made possible new methods that are impractical to perform manually.

Overview

In applying statistics to a scientific, industrial, or societal problem, it is necessary to begin with a population or process to be studied. Populations can be diverse topics such as "all persons living in a country" or "every atom composing a crystal". A population can also be composed of observations of a process at various times, with the data from each observation serving as a different member of the overall group. Data collected about this kind of "population" constitutes what is called a time series.
For practical reasons, a chosen subset of the population called a sample is studied — as opposed to compiling data about the entire group (an operation called census). Once a sample that is representative of the population is determined, data is collected for the sample members in an observational or experimental setting. This data can then be subjected to statistical analysis, serving two related purposes: description and inference.

• Descriptive statistics summarize the population data by describing what was observed in the sample numerically or graphically. Numerical descriptors include mean and standard deviation for continuous data types (like heights or weights), while frequency and percentage are more useful in terms of describing categorical data (like race).
• Inferential statistics uses patterns in the sample data to draw inferences about the population represented, accounting for randomness. These inferences may take the form of: answering yes/no questions about the data (hypothesis testing), estimating numerical characteristics of the data (estimation), describing associations within the data (correlation) and modeling relationships within the data (for example, using regression analysis). Inference can extend to forecasting, prediction and estimation of unobserved values either in or associated with the population being studied; it can include extrapolation and interpolation of time series or spatial data, and can also include data mining.^[14]

"... it is only the manipulation of uncertainty that interests us. We are not concerned with the matter that is uncertain. Thus we do not study the mechanism of rain; only whether it will rain."

Dennis Lindley, 2000^[15]

The concept of correlation is particularly noteworthy for the potential confusion it can cause. Statistical analysis of a data set often reveals that two variables (properties) of the population under consideration tend to vary together, as if they were connected. For example, a study of annual income that also looks at age of death might find that poor people tend to have shorter lives than affluent people. The two variables are said to be correlated; however, they may or may not be the cause of one another. The correlation phenomena could be caused by a third, previously unconsidered phenomenon, called a lurking variable or confounding variable. For this reason, there is no way to immediately infer the existence of a causal relationship between the two variables. (See Correlation does not imply causation.)
For a sample to be used as a guide to an entire population, it is important that it is truly a representative of that overall population. Representative sampling assures that the inferences and conclusions can be safely extended from the sample to the population as a whole. A major problem lies in determining the extent to which the sample chosen is actually representative. Statistics offers methods to estimate and correct for any random trending within the sample and data collection procedures. There are also methods of experimental design for experiments that can lessen these issues at the outset of a study, strengthening its capability to discern truths about the population.
Randomness is studied using the mathematical discipline of probability theory. Probability is used in "mathematical statistics" (alternatively, "statistical theory") to study the sampling distributions of sample statistics and, more generally, the properties of statistical procedures. The use of any statistical method is valid when the system or population under consideration satisfies the assumptions of the method.
Misuse of statistics can produce subtle, but serious errors in description and interpretation — subtle in the sense that even experienced professionals make such errors, and serious in the sense that they can lead to devastating decision errors. For instance, social policy, medical practice, and the reliability of structures like bridges all rely on the proper use of statistics. See below for further discussion.
Even when statistical techniques are correctly applied, the results can be difficult to interpret for those lacking expertise. The statistical significance of a trend in the data — which measures the extent to which a trend could be caused by random variation in the sample — may or may not agree with an intuitive sense of its significance. The set of basic statistical skills (and skepticism) that people need to deal with information in their everyday lives properly is referred to as statistical literacy.

Statistical methods

Experimental and observational studies

A common goal for a statistical research project is to investigate causality, and in particular to draw a conclusion on the effect of changes in the values of predictors or independent variables on dependent variables or response. There are two major types of causal statistical studies: experimental studies and observational studies. In both types of studies, the effect of differences of an independent variable (or variables) on the behavior of the dependent variable are observed. The difference between the two types lies in how the study is actually conducted. Each can be very effective. An experimental study involves taking measurements of the system under study, manipulating the system, and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements. In contrast, an observational study does not involve experimental manipulation. Instead, data are gathered and correlations between predictors and response are investigated.

Experiments

The basic steps of a statistical experiment are:

1. Planning the research, including finding the number of replicates of the study, using the following information: preliminary estimates regarding the size of treatment effects, alternative hypotheses, and the estimated experimental variability. Consideration of the selection of experimental subjects and the ethics of research is necessary. Statisticians recommend that experiments compare (at least) one new treatment with a standard treatment or control, to allow an unbiased estimate of the difference in treatment effects.
2. Design of experiments, using blocking to reduce the influence of confounding variables, and randomized assignment of treatments to subjects to allow unbiased estimates of treatment effects and experimental error. At this stage, the experimenters and statisticians write the experimental protocol that shall guide the performance of the experiment and that specifies the primary analysis of the experimental data.
3. Performing the experiment following the experimental protocol and analyzing the data following the experimental protocol.
4. Further examining the data set in secondary analyses, to suggest new hypotheses for future study.
5. Documenting and presenting the results of the study.

Experiments on human behavior have special concerns. The famous Hawthorne study examined changes to the working environment at the Hawthorne plant of the Western Electric Company. The researchers were interested in determining whether increased illumination would increase the productivity of the assembly line workers. The researchers first measured the productivity in the plant, then modified the illumination in an area of the plant and checked if the changes in illumination affected productivity. It turned out that productivity indeed improved (under the experimental conditions). However, the study is heavily criticized today for errors in experimental procedures, specifically for the lack of a control group and blindness. The Hawthorne effect refers to finding that an outcome (in this case, worker productivity) changed due to observation itself. Those in the Hawthorne study became more productive not because the lighting was changed but because they were being observed.^{[citation needed]}

Observational study

An example of an observational study is one that explores the correlation between smoking and lung cancer. This type of study typically uses a survey to collect observations about the area of interest and then performs statistical analysis. In this case, the researchers would collect observations of both smokers and non-smokers, perhaps through a case-control study, and then look for the number of cases of lung cancer in each group.

Levels of measurement

Main article: levels of measurement

There are four main levels of measurement used in statistics: nominal, ordinal, interval, and ratio.^[16] Each of these have different degrees of usefulness in statistical research. Ratio measurements have both a meaningful zero value and the distances between different measurements defined; they provide the greatest flexibility in statistical methods that can be used for analyzing the data.^{[citation needed]} Interval measurements have meaningful distances between measurements defined, but the zero value is arbitrary (as in the case with longitude and temperature measurements in Celsius or Fahrenheit). Ordinal measurements have imprecise differences between consecutive values, but have a meaningful order to those values. Nominal measurements have no meaningful rank order among values.
Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically, sometimes they are grouped together as categorical variables, whereas ratio and interval measurements are grouped together as quantitative variables, which can be either discrete or continuous, due to their numerical nature.

Key terms used in statistics

Null hypothesis

Interpretation of statistical information can often involve the development of a null hypothesis in that the assumption is that whatever is proposed as a cause has no effect on the variable being measured.
The best illustration for a novice is the predicament encountered by a jury trial. The null hypothesis, H₀, asserts that the defendant is innocent, whereas the alternative hypothesis, H₁, asserts that the defendant is guilty. The indictment comes because of suspicion of the guilt. The H₀ (status quo) stands in opposition to H₁ and is maintained unless H₁ is supported by evidence"beyond a reasonable doubt". However,"failure to reject H₀" in this case does not imply innocence, but merely that the evidence was insufficient to convict. So the jury does not necessarily accept H₀ but fails to reject H₀. While one can not "prove" a null hypothesis one can test how close it is to being true with a power test, which tests for type II errors.

Error

Working from a null hypothesis two basic forms of error are recognized:

• Type I errors where the null hypothesis is falsely rejected giving a "false positive".
• Type II errors where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a "false negative".

Error also refers to the extent to which individual observations in a sample differ from a central value, such as the sample or population mean. Many statistical methods seek to minimize the mean-squared error, and these are called "methods of least squares."
Measurement processes that generate statistical data are also subject to error. Many of these errors are classified as random (noise) or systematic (bias), but other important types of errors (e.g., blunder, such as when an analyst reports incorrect units) can also be important.

Interval estimation

Main article: interval estimation

Most studies will only sample part of a population and so the results are not fully representative of the whole population. Any estimates obtained from the sample only approximate the population value. Confidence intervals allow statisticians to express how closely the sample estimate matches the true value in the whole population. Often they are expressed as 95% confidence intervals. Formally, a 95% confidence interval for a value is a range where, if the sampling and analysis were repeated under the same conditions (yielding a different dataset), the interval would include the true (population) value 95% of the time. This does not imply that the probability that the true value is in the confidence interval is 95%. From the frequentist perspective, such a claim does not even make sense, as the true value is not a random variable. Either the true value is or is not within the given interval. However, it is true that, before any data are sampled and given a plan for how the confidence interval will be constructed, the probability is 95% that the yet-to-be-calculated interval will cover the true value: at this point, the limits of the interval are yet-to-be-observed random variables. One approach that does yield an interval that can be interpreted as having a given probability of containing the true value is to use a credible interval from Bayesian statistics: this approach depends on a different way of interpreting what is meant by "probability", that is as a Bayesian probability.

Significance

Main article: Statistical significance

This section includes a list of references, related reading or external links, but the sources of this section remain unclear because it lacks inline citations. Please improve this article by introducing more precise citations. (May 2012)

Statistics rarely give a simple Yes/No type answer to the question asked of them. Interpretation often comes down to the level of statistical significance applied to the numbers and often refers to the probability of a value accurately rejecting the null hypothesis (sometimes referred to as the p-value).
Referring to statistical significance does not necessarily mean that the overall result is significant in real world terms. For example, in a large study of a drug it may be shown that the drug has a statistically significant but very small beneficial effect, such that the drug will be unlikely to help the patient in a noticeable way.
Criticisms arise because the hypothesis testing approach forces one hypothesis (the null hypothesis) to be "favored," and can also seem to exaggerate the importance of minor differences in large studies. A difference that is highly statistically significant can still be of no practical significance, but it is possible to properly formulate tests in account for this. (See also criticism of hypothesis testing.)
One response involves going beyond reporting only the significance level to include the p-value when reporting whether a hypothesis is rejected or accepted. The p-value, however, does not indicate the size of the effect. A better and increasingly common approach is to report confidence intervals. Although these are produced from the same calculations as those of hypothesis tests or p-values, they describe both the size of the effect and the uncertainty surrounding it.