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Numerical Analysis
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Numerical analysis is the study of the methods used to solve problems ...

Numerical analysis is the study of the methods used to solve problems involving continuous variables. It is a highly applied branch of mathematics and computer science, wherein abstract ideas and theories become the quantities describing things we can actually touch and see. Suggested prerequisites for this course are MA211: Linear Algebra, MA221: Differential Equations, and either MA302/CS101: Introduction to Computer Science, or a background in some programming language. Programming ideas will be illustrated in pseudocode and implemented in the open-source high-level computing environment. Upon successful completion of this course, the student will be able to: show how numbers are represented on the computer, and how errors from this representation affect arithmetic; analyze errors and have an understanding of error estimation; be able to use polynomials in several ways to approximate both functions and data, and to match the type of polynomial approximation to a given type of problem; be able to solve equations in one unknown real variable using iterative methods and to understand how long these methods take to converge to a solution; derive formulas to approximate the derivative of a function at a point, and formulas to compute the definite integral of a function of one or more variables; choose and apply any of several modern methods for solving systems of initial value problems based on properties of the problem. This free course may be completed online at any time. (Mathematics 213)

Subject:
Computer Science
Functions
Material Type:
Assessments
Full Course
Readings
Syllabi
Video Lectures
Provider:
The Saylor Foundation
Data Quality: Missing Data
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This module describes how missing data can be managed while maintaining data ...

This module describes how missing data can be managed while maintaining data quality. It explains how to plan for missing data; defines different types of Ňmissingness;Ó outlines the benefits of documenting missing data and illustrates how to document missing data; and describes procedures to minimize missing data.

Subject:
Health, Medicine and Nursing
Material Type:
Assessments
Images and Illustrations
Lesson Plans
Unit of Study
Video Lectures
Provider:
OER Africa
University of Michigan
Provider Set:
open.Michigan African Health OER Network
Author:
Beverly Musick
Data Quality: Missing Data (PPT slides)
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This module describes how missing data can be managed while maintaining data ...

This module describes how missing data can be managed while maintaining data quality. It explains how to plan for missing data; defines different types of ˆmissingness;íń outlines the benefits of documenting missing data and illustrates how to document missing data; and describes procedures to minimize missing data. Upon completion of this module, students will be able to explain why data managers should strive to minimize missing data and develop a plan to record or code why data are missing.

Material Type:
Textbooks
Provider:
Global Health Informatics Partnership (GHIP)
OER Africa
Author:
Beverly Musick
IHME: Data Visualizations
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Institute for Health Metrics and Evaluation (IHME) strives to make its data ...

Institute for Health Metrics and Evaluation (IHME) strives to make its data freely and easily accessible and to provide innovative ways to visualize complex topics. Our data visualizations allow you to see patterns and follow trends that are not readily apparent in the numbers themselves. Here you can watch how trends in mortality change over time, choose countries to compare progress in a variety of health areas, or see how countries compare against each other on a global map.

Provider:
TeachingWithData.org
Provider Set:
TeachingWithData.org
Author:
IHME
Data Quality: Out of Range Values
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Defines what "Out of Range Values" are and how to account for ...

Defines what "Out of Range Values" are and how to account for them in data collection and statistical analysis.

Subject:
Health, Medicine and Nursing
Material Type:
Assessments
Images and Illustrations
Lesson Plans
Unit of Study
Video Lectures
Provider:
OER Africa
University of Michigan
Provider Set:
open.Michigan African Health OER Network
Author:
Beverly Musick
NOAA: National Environmental Satellite, Data, and Information Service
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No Strings Attached
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This website is the homepage of NOAA's environmental satellite monitoring service. The ...

This website is the homepage of NOAA's environmental satellite monitoring service. The National Environmental Satellite, Data, and Information Service (NESDIS) provides timely access to global environmental data from satellites and other sources to promote, protect, & enhance the Nation's economy, security, environment, & quality of life. The site features satellite and in situ data from NOAA's Climactic, Coastal, Geophysical, and Oceanographic Data Centers, satellite imagery and research, as well as information for students and educators.

Subject:
Geology
Physics
Material Type:
Readings
Provider:
NOAA
Author:
NOAA
Ocean View Data Visualization Tool
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The Ocean View Data Visualization Tool is an interactive, online, data-display tool ...

The Ocean View Data Visualization Tool is an interactive, online, data-display tool that helps students understand real-world environmental problems using advanced technology and inquiry.

Subject:
Chemistry
Material Type:
Activities and Labs
Data
Instructional Material
Simulations
Student Guide
Provider:
iLumina
Provider Set:
iLumina Digital Library
Author:
Dr. Richard Huber
Fowler Lauren Marie
Lea Bullard
Valios Kevin
RiverView Data Visualization Tool
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The RiverView Data Visualization Tool is an interactive, online, data-display tool that ...

The RiverView Data Visualization Tool is an interactive, online, data-display tool that helps students understand real-world environmental problems using advanced technology and inquiry.

Subject:
Biology
Ecology
Chemistry
Material Type:
Activities and Labs
Data
Instructional Material
Simulations
Student Guide
Provider:
iLumina
Provider Set:
iLumina Digital Library
Author:
Dr. Richard Huber
Lea Bullard
New River Data Visualization Tools
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The New River Data Visualization Tools are interactive, online, data-display tools that ...

The New River Data Visualization Tools are interactive, online, data-display tools that help students understand real-world environmental problems using advanced technology and inquiry.

Subject:
Biology
Ecology
Chemistry
Material Type:
Activities and Labs
Data
Instructional Material
Lesson Plans
Simulations
Student Guide
Provider:
iLumina
Provider Set:
iLumina Digital Library
Author:
Dr. Richard Huber
Lea Bullard
River Run Data Visualization Tool
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The River Run Data Visualization Tool is an interactive, online, data-display tool ...

The River Run Data Visualization Tool is an interactive, online, data-display tool that helps students understand real-world environmental problems using advanced technology and inquiry.

Subject:
Ecology
Forestry and Agriculture
Material Type:
Activities and Labs
Data
Instructional Material
Simulations
Student Guide
Provider:
iLumina
Provider Set:
iLumina Digital Library
Author:
Dr. Richard Huber
Lea Bullard
The Beauty of Data Visualization
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David McCandless turns complex data sets (like worldwide military spending, media buzz, ...

David McCandless turns complex data sets (like worldwide military spending, media buzz, Facebook status updates) into beautiful, simple diagrams that tease out unseen patterns and connections. Good design, he suggests, is the best way to navigate information glut -- and it may just change the way we see the world. A quiz, thought provoking question, and links for further study are provided to create a lesson around the 18-minute video. Educators may use the platform to easily "Flip" or create their own lesson for use with their students of any age or level.

Subject:
Journalism
Material Type:
Video Lectures
Provider:
TED
Provider Set:
TED-Ed
Author:
McCandless, David
Data Quality Out of Range Values PowerPoint
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Defines what Out of Range Values are and how to account for ...

Defines what Out of Range Values are and how to account for them in data collection and statistical analysis.Competencies/Skills that HIBB Addresses: Understand how to minimize out of range values when creating new data sets.

Material Type:
Textbooks
Provider:
Global Health Informatics Partnership (GHIP)
OER Africa
Author:
Beverly Musick
Prediction: Machine Learning and Statistics, Spring 2012
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Prediction is at the heart of almost every scientific discipline, and the ...

Prediction is at the heart of almost every scientific discipline, and the study of generalization (that is, prediction) from data is the central topic of machine learning and statistics, and more generally, data mining. Machine learning and statistical methods are used throughout the scientific world for their use in handling the "information overload" that characterizes our current digital age. Machine learning developed from the artificial intelligence community, mainly within the last 30 years, at the same time that statistics has made major advances due to the availability of modern computing. However, parts of these two fields aim at the same goal, that is, of prediction from data. This course provides a selection of the most important topics from both of these subjects.

Subject:
Business and Communication
Statistics and Probability
Material Type:
Full Course
Homework and Assignments
Lecture Notes
Syllabi
Provider:
M.I.T.
Provider Set:
M.I.T. OpenCourseWare
Author:
Cynthia Rudin
Introduction to Ensemble Prediction
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This webcast is a shorter companion to the Ensemble Prediction Explained module, ...

This webcast is a shorter companion to the Ensemble Prediction Explained module, focusing more directly on immediate operational needs. Introductory content includes the role of ensemble forecasts, presentation of basic ensemble forecasting terms, and discussion of how ensemble prediction systems (EPSs) are created. The largest section is focused on common ensemble forecast products, including how they differ from traditional NWP products, how we interpret ensemble forecast products, the advantages and limitations of each product, how EPS products are verified, and how to use ensemble products in conjunction with one another to increase your understanding of forecast uncertainty. Finally, three brief cases from cold and warm seasons illustrate the use of ensemble products in the forecast process.

Subject:
Atmospheric Science
Material Type:
Instructional Material
Provider:
UCAR
UCAR Staff
Provider Set:
COMET/MetEd Program Collection
Author:
COMET