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UCLA Graduate School Of Education And Information Studies
Information
Information
is any entity or form that resolves uncertainty or provides the answer to a question of some kind. It is thus related to data and knowledge, as data represents values attributed to parameters, and knowledge signifies understanding of real things or abstract concepts.[1] As it regards data, the information's existence is not necessarily coupled to an observer (it exists beyond an event horizon, for example), while in the case of knowledge, the information requires a cognitive observer.[citation needed] Information
Information
is conveyed either as the content of a message or through direct or indirect observation
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Dagbladet Information
Information (Danish pronunciation: [enfɒmæˈɕoːˀn]), full name: Dagbladet Information ([ˈdɑwˌblæːˀð enfɒmæˈɕoːˀn]), is a Danish newspaper published Monday through Saturday.Contents1 History and profile 2 Circulation 3 References 4 External linksHistory and profile[edit] Dagbladet Information was established and published by the Danish resistance movement in 1943 during World War II.[1][2] The paper was edited by Børge Outze[3] and was illegal during the war as it was not regulated by the German occupying power.[2][3] Following the liberation on 5 May 1945 Dagbladet Information was a reality and was officially founded in August 1945.[2] Outze continued to work as the paper's editor in chief to his death in 1980
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Infographic
Infographics (a clipped compound of "information" and "graphics") are graphic visual representations of information, data or knowledge intended to present information quickly and clearly.[1][2] They can improve cognition by utilizing graphics to enhance the human visual system’s ability to see patterns and trends.[3][4] Similar pursuits are information visualization, data visualization, statistical graphics, information design, or information architecture.[2] Infographics have evolved in recent years to be for mass communication, and thus are designed with fewer assumptions about the readers' knowledge base than other types of visualizations
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Statistics
Statistics
Statistics
is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data.[1][2] In applying statistics to, for example, a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model process to be studied. Populations can be diverse topics such as "all people living in a country" or "every atom composing a crystal". Statistics
Statistics
deals with all aspects of data including the planning of data collection in terms of the design of surveys and experiments.[1] See glossary of probability and statistics. When census data cannot be collected, statisticians collect data by developing specific experiment designs and survey samples. Representative sampling assures that inferences and conclusions can reasonably extend from the sample to the population as a whole
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Data Visualization
Data
Data
visualization or data visualisation is viewed by many disciplines as a modern equivalent of visual communication. It involves the creation and study of the visual representation of data, meaning "information that has been abstracted in some schematic form, including attributes or variables for the units of information".[1] A primary goal of data visualization is to communicate information clearly and efficiently via statistical graphics, plots and information graphics
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Exploratory Data Analysis
In statistics, exploratory data analysis (EDA) is an approach to analyzing data sets to summarize their main characteristics, often with visual methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling or hypothesis testing task. Exploratory data analysis was promoted by John Tukey
John Tukey
to encourage statisticians to explore the data, and possibly formulate hypotheses that could lead to new data collection and experiments. EDA is different from initial data analysis (IDA),[1] which focuses more narrowly on checking assumptions required for model fitting and hypothesis testing, and handling missing values and making transformations of variables as needed
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Information Design
Information
Information
design is the practice of presenting information in a way that fosters efficient and effective understanding of it. The term has come to be used specifically for graphic design for displaying information effectively, rather than just attractively or for artistic expression. Information
Information
design is closely related to the field of data visualization and is often taught as part of graphic design courses.[1] Information
Information
design is explanation design. It explains facts of the universe and leads to knowledge and informed action.[2]Contents1 History 2 Early examples 3 Applications 4 Simplicity 5 See also 6 References 7 External linksHistory[edit] The term 'information design' emerged as a multidisciplinary area of study in the 1970s
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Interactive Data Visualization
interactive data visualization enables direct actions on a plot to change elements and link between multiple plots.[1]Contents1 Overview 2 Common interactions 3 See also 4 ReferencesOverview[edit] Interactive data visualization
Interactive data visualization
has been a pursuit of statisticians since the late 1960s. Examples of the developments can be found on the ASA video lending library.[2] Common interactions[edit]Brushing: works by using the mouse to control a paintbrush, directly changing the color or glyph of elements of a plot. The paintbrush is sometimes a pointer and sometimes works by drawing an outline of sorts around points; the outline is sometimes irregularly shaped, like a lasso. Brushing is most commonly used when multiple plots are visible and some linking mechanism exists between the plots. There are several different conceptual models for brushing and a number of common linking mechanisms
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Descriptive Statistics
A descriptive statistic (in the count noun sense) is a summary statistic that quantitatively describes or summarizes features of a collection of information,[1] while descriptive statistics in the mass noun sense is the process of using and analyzing those statistics. Descriptive statistics is distinguished from inferential statistics (or inductive statistics), in that descriptive statistics aims to summarize a sample, rather than use the data to learn about the population that the sample of data is thought to represent. This generally means that descriptive statistics, unlike inferential statistics, is not developed on the basis of probability theory.[2] Even when a data analysis draws its main conclusions using inferential statistics, descriptive statistics are generally also presented
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Statistical Inference
Statistical inference is the process of using data analysis to deduce properties of an underlying probability distribution.[1] Inferential statistical analysis infers properties of a population, for example by testing hypotheses and deriving estimates
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Statistical Graphics
Statistical graphics, also known as graphical techniques, are graphics in the field of statistics used to visualize quantitative data.Contents1 Overview 2 History 3 Examples 4 See also 5 References 6 Further reading 7 External linksOverview[edit] Whereas statistics and data analysis procedures generally yield their output in numeric or tabular form, graphical techniques allow such results to be displayed in some sort of pictorial form. They include plots such as scatter plots, histograms, probability plots, spaghetti plots, residual plots, box plots, block plots and biplots.[1] Exploratory data analysis
Exploratory data analysis
(EDA) relies heavily on such techniques. They can also provide insight into a data set to help with testing assumptions, model selection and regression model validation, estimator selection, relationship identification, factor effect determination, and outlier detection
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Plot (graphics)
A plot is a graphical technique for representing a data set, usually as a graph showing the relationship between two or more variables. The plot can be drawn by hand or by a mechanical or electronic plotter. Graphs are a visual representation of the relationship between variables, very useful for humans who can quickly derive an understanding which would not come from lists of values. Graphs can also be used to read off the value of an unknown variable plotted as a function of a known one. Graphs of functions are used in mathematics, sciences, engineering, technology, finance, and other areas.Contents1 Overview 2 Types of Plots 3 Examples 4 See also 5 References 6 External linksOverview[edit] Plots play an important role in statistics and data analysis. The procedures here can broadly be split into two parts: quantitative and graphical. Quantitative techniques are the set of statistical procedures that yield numeric or tabular output
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Data Analysis
Numerical analysis · Simulation Data
Data
analysis · VisualizationPotentials Morse/Long-range potential · Lennard-Jones potential · Yukawa potential · Morse potentialFluid dynamics Finite difference · Finite volume Finite element · Boundary element Lattice Boltzmann · Riemann solver Dissipative particle dynamics Smoothed particle hydrodynamics Turbulence modelsMonte Carlo methods Integration · Gibbs sampling · Metropolis algorithmParticle N-body · Particle-in-cell Molecular dynamicsScientists Godunov · Ulam · von Neumann · Galerkin · Lorenz · Wilsonv t e Data
Data
analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making
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Data Science
Data
Data
science, also known as data-driven science, is an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms, either structured or unstructured,[1][2] similar to data mining. Data
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Literature
Literature, most generically, is any body of written works. More restrictively, literature is writing considered to be an art form, or any single writing deemed to have artistic or intellectual value, often due to deploying language in ways that differ from ordinary usage. Its Latin root literatura/litteratura (derived itself from littera: letter or handwriting) was used to refer to all written accounts, though contemporary definitions extend the term to include texts that are spoken or sung (oral literature). The concept has changed meaning over time: nowadays it can broaden to have non-written verbal art forms, and thus it is difficult to agree on its origin, which can be paired with that of language or writing itself
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Tamara Munzner
Tamara Macushla Munzner (born 1969)[1] is an expert in information visualization who works as a professor of computer science at the University of British Columbia
University of British Columbia
(UBC).[2] Munzner earned a bachelor's degree in computer science from Stanford University in 1991, then worked at The Geometry Center at the University of Minnesota
University of Minnesota
from 1991 to 1995.[2] There, she helped produce two mathematical visualization videos, one about turning spheres inside-out and another about the different topological structures that a three-dimensional universe could have.[3] She returned to Stanford for her graduate studies, completing her Ph.D
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