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12.010 Computational Methods of Scientific Programming (MIT) 12.010 Computational Methods of Scientific Programming (MIT)

Description

This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB, and Mathematica. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages. This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB, and Mathematica. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages.

Subjects

programming languages | programming languages | techniques used by physical scientists | techniques used by physical scientists | FORTRAN | FORTRAN | C | C | C++ | C++ | Matlab | Matlab | Mathematica | Mathematica | program design | program design | algorithm development and verification | algorithm development and verification | comparative advantages and disadvantages of different languages | comparative advantages and disadvantages of different languages | examination of data with visualization techniques | examination of data with visualization techniques | numerical analysis | numerical analysis | methods of dissemination and verification | methods of dissemination and verification

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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18.06 Linear Algebra (MIT) 18.06 Linear Algebra (MIT)

Description

This is a basic subject on matrix theory and linear algebra. Emphasis is given to topics that will be useful in other disciplines, including systems of equations, vector spaces, determinants, eigenvalues, similarity, and positive definite matrices. This is a basic subject on matrix theory and linear algebra. Emphasis is given to topics that will be useful in other disciplines, including systems of equations, vector spaces, determinants, eigenvalues, similarity, and positive definite matrices.

Subjects

Generalized spaces | Generalized spaces | Linear algebra | Linear algebra | Algebra | Universal | Algebra | Universal | Mathematical analysis | Mathematical analysis | Calculus of operations | Calculus of operations | Line geometry | Line geometry | Topology | Topology | matrix theory | matrix theory | systems of equations | systems of equations | vector spaces | vector spaces | systems determinants | systems determinants | eigen values | eigen values | positive definite matrices | positive definite matrices | Markov processes | Markov processes | Fourier transforms | Fourier transforms | differential equations | differential equations | linear algebra | linear algebra | determinants | determinants | eigenvalues | eigenvalues | similarity | similarity | least-squares approximations | least-squares approximations | stability of differential equations | stability of differential equations | networks | networks

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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12.010 Computational Methods of Scientific Programming (MIT) 12.010 Computational Methods of Scientific Programming (MIT)

Description

This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB, and Mathematica. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages. This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB, and Mathematica. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages.

Subjects

programming languages | programming languages | techniques used by physical scientists | techniques used by physical scientists | FORTRAN | FORTRAN | C | C | C++ | C++ | Matlab | Matlab | Mathematica | Mathematica | program design | program design | algorithm development and verification | algorithm development and verification | comparative advantages and disadvantages of different languages | comparative advantages and disadvantages of different languages | examination of data with visualization techniques | examination of data with visualization techniques | numerical analysis | numerical analysis | methods of dissemination and verification | methods of dissemination and verification

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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12.010 Computational Methods of Scientific Programming (MIT) 12.010 Computational Methods of Scientific Programming (MIT)

Description

This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB®, and Mathematica®. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages. This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB®, and Mathematica®. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages.

Subjects

programming languages | programming languages | techniques used by physical scientists | techniques used by physical scientists | FORTRAN | FORTRAN | C | C | C++; Matlab | C++; Matlab | Mathematica | Mathematica | program design | program design | algorithm development and verification | algorithm development and verification | comparative advantages and disadvantages of different languages | comparative advantages and disadvantages of different languages | examination of data with visualization techniques | examination of data with visualization techniques | numerical analysis | numerical analysis | methods of dissemination and verification. | methods of dissemination and verification. | C++ | C++ | Matlab | Matlab | programming languages | techniques used by physical scientists | programming languages | techniques used by physical scientists

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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12.010 Computational Methods of Scientific Programming (MIT) 12.010 Computational Methods of Scientific Programming (MIT)

Description

This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB®, and Mathematica®. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages. Students first learn the basic usage of each language, common types of problems encountered, and techniques for solving a variety of problems encountered in contemporary research: examination of data with visualization techniques, numerical analysis, and methods of dissemination and verification. No prior programming experience is required.Technical RequirementsAny number of development tools can be used to compile and run the .c and .f files found on this course site. C++ compiler is required to This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB®, and Mathematica®. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages. Students first learn the basic usage of each language, common types of problems encountered, and techniques for solving a variety of problems encountered in contemporary research: examination of data with visualization techniques, numerical analysis, and methods of dissemination and verification. No prior programming experience is required.Technical RequirementsAny number of development tools can be used to compile and run the .c and .f files found on this course site. C++ compiler is required to

Subjects

programming languages | techniques used by physical scientists | programming languages | techniques used by physical scientists | FORTRAN | FORTRAN | C | C | C++ | C++ | Matlab | Matlab | Mathematica | Mathematica | program design | program design | algorithm development and verification | algorithm development and verification | comparative advantages and disadvantages of different languages | comparative advantages and disadvantages of different languages | examination of data with visualization techniques | examination of data with visualization techniques | numerical analysis | numerical analysis | methods of dissemination and verification | methods of dissemination and verification | algorithms | algorithms | formula | formula | formulae | formulae | computer programs | computer programs | graphics | graphics | computing languages | computing languages | structure | structure | documentation | documentation | program interface | program interface | syntax | syntax | advanced modeling | advanced modeling | simulation systems | simulation systems

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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18.06 Linear Algebra (MIT) 18.06 Linear Algebra (MIT)

Description

Basic subject on matrix theory and linear algebra, emphasizing topics useful in other disciplines, including systems of equations, vector spaces, determinants, eigenvalues, similarity, and positive definite matrices. Applications to least-squares approximations, stability of differential equations, networks, Fourier transforms, and Markov processes. Uses MATLAB®. Compared with 18.700 [also Linear Algebra], more emphasis on matrix algorithms and many applications. MATLAB® is a trademark of The MathWorks, Inc. Basic subject on matrix theory and linear algebra, emphasizing topics useful in other disciplines, including systems of equations, vector spaces, determinants, eigenvalues, similarity, and positive definite matrices. Applications to least-squares approximations, stability of differential equations, networks, Fourier transforms, and Markov processes. Uses MATLAB®. Compared with 18.700 [also Linear Algebra], more emphasis on matrix algorithms and many applications. MATLAB® is a trademark of The MathWorks, Inc.

Subjects

Generalized spaces | Generalized spaces | Linear algebra | Linear algebra | Algebra | Universal | Algebra | Universal | Mathematical analysis | Mathematical analysis | Calculus of operations | Calculus of operations | Line geometry | Line geometry | Topology | Topology | matrix theory | matrix theory | systems of equations | systems of equations | vector spaces | vector spaces | systems determinants | systems determinants | eigen values | eigen values | positive definite matrices | positive definite matrices | Markov processes | Markov processes | Fourier transforms | Fourier transforms | differential equations | differential equations

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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15.094 Systems Optimization: Models and Computation (MIT) 15.094 Systems Optimization: Models and Computation (MIT)

Description

An applications-oriented course on the modeling of large-scale systems in decision-making domains and the optimization of such systems using state-of-the-art optimization tools. Application domains include: transportation and logistics planning, pattern classification and image processing, data mining, design of structures, scheduling in large systems, supply-chain management, financial engineering, and telecommunications systems planning. Modeling tools and techniques include linear, network, discrete and nonlinear optimization, heuristic methods, sensitivity and post-optimality analysis, decomposition methods for large-scale systems, and stochastic optimization. An applications-oriented course on the modeling of large-scale systems in decision-making domains and the optimization of such systems using state-of-the-art optimization tools. Application domains include: transportation and logistics planning, pattern classification and image processing, data mining, design of structures, scheduling in large systems, supply-chain management, financial engineering, and telecommunications systems planning. Modeling tools and techniques include linear, network, discrete and nonlinear optimization, heuristic methods, sensitivity and post-optimality analysis, decomposition methods for large-scale systems, and stochastic optimization.

Subjects

telecommunications system planning | telecommunications system planning | modeling of large-scale systems | modeling of large-scale systems | optimization software | optimization software | management | management | decision making | decision making | Mathematical optimization | Mathematical optimization

License

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3.016 Mathematics for Materials Scientists and Engineers (MIT) 3.016 Mathematics for Materials Scientists and Engineers (MIT)

Description

This course covers the mathematical techniques necessary for understanding of materials science and engineering topics such as energetics, materials structure and symmetry, materials response to applied fields, mechanics and physics of solids and soft materials. The class uses examples from the materials science and engineering core courses (3.012 and 3.014) to introduce mathematical concepts and materials-related problem solving skills. Topics include linear algebra and orthonormal basis, eigenvalues and eigenvectors, quadratic forms, tensor operations, symmetry operations, calculus of several variables, introduction to complex analysis, ordinary and partial differential equations, theory of distributions, and fourier analysis. Users may find additional or updated materials at Professor C This course covers the mathematical techniques necessary for understanding of materials science and engineering topics such as energetics, materials structure and symmetry, materials response to applied fields, mechanics and physics of solids and soft materials. The class uses examples from the materials science and engineering core courses (3.012 and 3.014) to introduce mathematical concepts and materials-related problem solving skills. Topics include linear algebra and orthonormal basis, eigenvalues and eigenvectors, quadratic forms, tensor operations, symmetry operations, calculus of several variables, introduction to complex analysis, ordinary and partial differential equations, theory of distributions, and fourier analysis. Users may find additional or updated materials at Professor C

Subjects

energetics | energetics | visualization | visualization | graph | graph | plot | plot | chart | chart | materials science | materials science | DMSE | DMSE | structure | structure | symmetry | symmetry | mechanics | mechanics | physicss | physicss | solids and soft materials | solids and soft materials | linear algebra | linear algebra | orthonormal basis | orthonormal basis | eigenvalue | eigenvalue | eigenvector | eigenvector | quadratic form | quadratic form | tensor operation | tensor operation | symmetry operation | symmetry operation | calculus | calculus | complex analysis | complex analysis | differential equations | differential equations | ODE | ODE | solution | solution | vector | vector | matrix | matrix | determinant | determinant | theory of distributions | theory of distributions | fourier analysis | fourier analysis | random walk | random walk | Mathematica | Mathematica | simulation | simulation

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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12.010 Computational Methods of Scientific Programming (MIT) 12.010 Computational Methods of Scientific Programming (MIT)

Description

This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB®, and Mathematica. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages. This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB®, and Mathematica. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages.

Subjects

FORTRAN | FORTRAN | C | C | C++ | C++ | Matlab | Matlab | Mathematica | Mathematica | program design | program design | algorithm development and verification | algorithm development and verification | visualization techniques | visualization techniques | numerical analysis | numerical analysis | dissemination | dissemination

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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15.094J Systems Optimization: Models and Computation (SMA 5223) (MIT) 15.094J Systems Optimization: Models and Computation (SMA 5223) (MIT)

Description

This class is an applications-oriented course covering the modeling of large-scale systems in decision-making domains and the optimization of such systems using state-of-the-art optimization tools. Application domains include: transportation and logistics planning, pattern classification and image processing, data mining, design of structures, scheduling in large systems, supply-chain management, financial engineering, and telecommunications systems planning. Modeling tools and techniques include linear, network, discrete and nonlinear optimization, heuristic methods, sensitivity and post-optimality analysis, decomposition methods for large-scale systems, and stochastic optimization. This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5223 This class is an applications-oriented course covering the modeling of large-scale systems in decision-making domains and the optimization of such systems using state-of-the-art optimization tools. Application domains include: transportation and logistics planning, pattern classification and image processing, data mining, design of structures, scheduling in large systems, supply-chain management, financial engineering, and telecommunications systems planning. Modeling tools and techniques include linear, network, discrete and nonlinear optimization, heuristic methods, sensitivity and post-optimality analysis, decomposition methods for large-scale systems, and stochastic optimization. This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5223

Subjects

decision making | decision making | management | management | Mathematical optimization | Mathematical optimization | modeling of large-scale system | modeling of large-scale system | optimization software | optimization software | telecommunications system planning | telecommunications system planning | 15.094 | 15.094 | 1.142 | 1.142 | SMA 5223 | SMA 5223

License

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Quantum field theory Quantum field theory

Description

This is a module framework. It can be viewed online or downloaded as a zip file. Last taught in Spring Semester 2006 A compilation of fourteen lectures in PDF format on the subject of quantum field theory. This module is suitable for 3rd or 4th year undergraduate and postgraduate level learners. Suitable for year 3/4 undergraduate and postgraduate study. Dr Kirill Krasnov, School of Mathematical Sciences Dr Kirill Krasnov is a Lecturer at the University of Nottingham. After studying physics in Kiev, Ukraine, he carried out research for his doctorate at Pennsylvania State University, USA and then held post-doctoral positions at University of California, Santa Barbara and Max Planck Institute for Gravitational Physics, Germany. His main research interest is in the field of quantum grav This is a module framework. It can be viewed online or downloaded as a zip file. Last taught in Spring Semester 2006 A compilation of fourteen lectures in PDF format on the subject of quantum field theory. This module is suitable for 3rd or 4th year undergraduate and postgraduate level learners. Suitable for year 3/4 undergraduate and postgraduate study. Dr Kirill Krasnov, School of Mathematical Sciences Dr Kirill Krasnov is a Lecturer at the University of Nottingham. After studying physics in Kiev, Ukraine, he carried out research for his doctorate at Pennsylvania State University, USA and then held post-doctoral positions at University of California, Santa Barbara and Max Planck Institute for Gravitational Physics, Germany. His main research interest is in the field of quantum grav

Subjects

UNow | UNow | UKOER | UKOER | Quantum Field Theory | Quantum Field Theory | Relativistic Fields | Relativistic Fields | Quantization | Quantization | Feynman Path Integral | Feynman Path Integral | Renormalization | Renormalization | Physical Sciences | Physical Sciences | Physics | Physics | Mathematical and Theoretical Physics | Mathematical and Theoretical Physics

License

Except for third party materials (materials owned by someone other than The University of Nottingham) and where otherwise indicated, the copyright in the content provided in this resource is owned by The University of Nottingham and licensed under a Creative Commons Attribution-NonCommercial-ShareAlike UK 2.0 Licence (BY-NC-SA) Except for third party materials (materials owned by someone other than The University of Nottingham) and where otherwise indicated, the copyright in the content provided in this resource is owned by The University of Nottingham and licensed under a Creative Commons Attribution-NonCommercial-ShareAlike UK 2.0 Licence (BY-NC-SA)

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Why do we do proofs? Why do we do proofs?

Description

The aim of this session is to motivate students to understand why we might want to do proofs, why proofs are important, and how they can help us. In particular, the student will learn the following: proofs can help you to really see WHY a result is true; problems that are easy to state can be hard to solve (Fermat's Last Theorem); sometimes statements which appear to be intuitively obvious may turn out to be false (the Hospitals paradox); the answer to a question will often depend crucially on the definitions you are working with. Target audience: suitable for anyone with a knowledge of elementary algebra and prime numbers, as may be obtained by studying A level mathematics. The aim of this session is to motivate students to understand why we might want to do proofs, why proofs are important, and how they can help us. In particular, the student will learn the following: proofs can help you to really see WHY a result is true; problems that are easy to state can be hard to solve (Fermat's Last Theorem); sometimes statements which appear to be intuitively obvious may turn out to be false (the Hospitals paradox); the answer to a question will often depend crucially on the definitions you are working with. Target audience: suitable for anyone with a knowledge of elementary algebra and prime numbers, as may be obtained by studying A level mathematics.

Subjects

UNow | UNow | Mathematical proofs | Mathematical proofs | UKOER | UKOER

License

Except for third party materials (materials owned by someone other than The University of Nottingham) and where otherwise indicated, the copyright in the content provided in this resource is owned by The University of Nottingham and licensed under a Creative Commons Attribution-NonCommercial-ShareAlike UK 2.0 Licence (BY-NC-SA) Except for third party materials (materials owned by someone other than The University of Nottingham) and where otherwise indicated, the copyright in the content provided in this resource is owned by The University of Nottingham and licensed under a Creative Commons Attribution-NonCommercial-ShareAlike UK 2.0 Licence (BY-NC-SA)

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21H.343J Making Books: The Renaissance and Today (MIT) 21H.343J Making Books: The Renaissance and Today (MIT)

Description

This course explores the impact of new technology on the recording and distribution of words and images at three different times: The invention of the printing press ca. 1450; the adaptation of electricity to communication technology in the 19th century (telegraph, telephone, phonograph); and the emergence of digital media today. Assignments include essays and online projects. Students also participate in the design and construction of a hand-set printing press. This course is also part of the Concourse program at MIT. This course explores the impact of new technology on the recording and distribution of words and images at three different times: The invention of the printing press ca. 1450; the adaptation of electricity to communication technology in the 19th century (telegraph, telephone, phonograph); and the emergence of digital media today. Assignments include essays and online projects. Students also participate in the design and construction of a hand-set printing press. This course is also part of the Concourse program at MIT.

Subjects

Gutenberg Bible | Gutenberg Bible | French Revolution | French Revolution | printing press | printing press | books | books | Renaissance period | Renaissance period | Early Modern period | Early Modern period | Gill and Edes | Gill and Edes | paper-making | paper-making | Book of Hours | Book of Hours | Nuremburg Chronicle | Nuremburg Chronicle | Decrees of Gregory IX | Decrees of Gregory IX | English Book of Martyrs | English Book of Martyrs | King James Bible | King James Bible | Lutheran Bible | Lutheran Bible | religion | religion | Hart Nautical Collection | Hart Nautical Collection | polyglot Bible | polyglot Bible | engraving | engraving | Ambroise Pare | Ambroise Pare | Gessner | Gessner | Galileo | Galileo | Tycho Brahe | Tycho Brahe | Spheres of Sacrobosco | Spheres of Sacrobosco | De Re Metallica | De Re Metallica | Mathematical Recreations | Mathematical Recreations | The Cheese and the Worms | The Cheese and the Worms | Menocchio | Menocchio | Domenico Scandella | Domenico Scandella

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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Percentages

Description

An introduction to percentages using the 2008 US presidential elections and some practical examples using shopping themes.

Subjects

maths | percentages | numeracy | mathematics | president | fractions | obama | Mathematical and Computer Sciences | Computer science | I100

License

Attribution-Share Alike 2.0 UK: England & Wales Attribution-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-sa/2.0/uk/ http://creativecommons.org/licenses/by-sa/2.0/uk/

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Probability and inferential statistics

Description

An introduction to probability and the probability of sample errors affecting research results

Subjects

evidence based practice | numeracy | study skills | probability | risk | Education | Subjects allied to Medicine | Mathematical and Computer Sciences | Computer science | Subjects allied to medicine | X000 | I100 | B000 | EDUCATION / TRAINING / TEACHING | G

License

Attribution-Share Alike 2.0 UK: England & Wales Attribution-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-sa/2.0/uk/ http://creativecommons.org/licenses/by-sa/2.0/uk/

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Recognising Nominative Categorative data

Description

B musicians.

Subjects

causes of death | nominative categorative data | statistics | data table | interpreting data | musicians | sociology | sociological methods | spreadsheet | Mathematical and Computer Sciences | Social studies | Computer science | I100 | L000

License

Attribution-Share Alike 2.0 UK: England & Wales Attribution-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-sa/2.0/uk/ http://creativecommons.org/licenses/by-sa/2.0/uk/

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Decimals

Description

To be completed A basic introduction to decimals.

Subjects

mathematics | maths | decimals | numeracy | to be completed | Biological Sciences | Mathematical and Computer Sciences | Biological sciences | Computer science | C000 | I100

License

Attribution-Share Alike 2.0 UK: England & Wales Attribution-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-sa/2.0/uk/ http://creativecommons.org/licenses/by-sa/2.0/uk/

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Descriptive statistics for interval and ratio scale

Description

Describes the use of measures of central tendency, mean, mode, median and dispersion - range, standard deviation

Subjects

descriptive statistics | numeracy | study skills | evidence based practice | Education | Subjects allied to Medicine | Mathematical and Computer Sciences | Computer science | Subjects allied to medicine | X000 | I100 | B000 | EDUCATION / TRAINING / TEACHING | G

License

Attribution-Share Alike 2.0 UK: England & Wales Attribution-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-sa/2.0/uk/ http://creativecommons.org/licenses/by-sa/2.0/uk/

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Fractions

Description

A basic introduction to fractions.

Subjects

maths | fractions | numeracy | Mathematical and Computer Sciences | Computer science | I100

License

Attribution-Share Alike 2.0 UK: England & Wales Attribution-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-sa/2.0/uk/ http://creativecommons.org/licenses/by-sa/2.0/uk/

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Arithmetic in Java 1 (Storing numbers)

Description

This is a simple learning object that illustrates how numbers are stored in the computer memory. It shows the effects of simple declaration and assignment statements. This object illustrates how memory is allocated and used to store numbers.

Subjects

numbers | arithmetic | java | Mathematical and Computer Sciences | Computer science | I100

License

Attribution-Share Alike 2.0 UK: England & Wales Attribution-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-sa/2.0/uk/ http://creativecommons.org/licenses/by-sa/2.0/uk/

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Arrays in Java (Arrays)

Description

Abstraction is a significant problem in learning to program. The learner has to relate the surface code to the operations in the memory of the computer. Visualisation of an ?array? is used here to help learners to form a mental concept that enables them to make sense of the surface code. A play-like drag and drop 'exercise' is used near the end to get the learner to actively test their understanding.

Subjects

arrays | programming | java | Mathematical and Computer Sciences | Computer science | I100

License

Attribution-Share Alike 2.0 UK: England & Wales Attribution-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-sa/2.0/uk/ http://creativecommons.org/licenses/by-sa/2.0/uk/

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While Loops

Description

This learning object seeks to engage the learner through attractive use of visualisation. As the subject is 'repetition' this is illustrated by using repeated actions to move an object across a screen. Redundancy is built in to help weaker students, but this may be bypassed. 'Scaffolding' is used near the end of the object to enable the learner to engage in building the programming construct in a safe supportive environment. This takes the form of building the code by selecting from code fragments provided.

Subjects

repetition | submarine | hammer | car | java | while loops | Mathematical and Computer Sciences | Computer science | I100

License

Attribution-Share Alike 2.0 UK: England & Wales Attribution-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-sa/2.0/uk/ http://creativecommons.org/licenses/by-sa/2.0/uk/

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Levels of Measurement

Description

To understand the different levels of measurement including nominal, ration, ordinal and scale measurements and the arithmetic operations that can be performed on them

Subjects

numeracy | study skills | evidence based practice | statistics | probability | risk | Education | Subjects allied to Medicine | Mathematical and Computer Sciences | Computer science | Subjects allied to medicine | X000 | I100 | B000 | EDUCATION / TRAINING / TEACHING | G

License

Attribution-Share Alike 2.0 UK: England & Wales Attribution-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-sa/2.0/uk/ http://creativecommons.org/licenses/by-sa/2.0/uk/

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Levels of Measurement - what you can and can't do arithmetically

Description

An explanation of the statistical operations that can be performed on the different levels of measurement.

Subjects

evidence based practice | statistics | numeracy | study skills | Education | Subjects allied to Medicine | Mathematical and Computer Sciences | Computer science | Subjects allied to medicine | X000 | I100 | B000 | EDUCATION / TRAINING / TEACHING | G

License

Attribution-Share Alike 2.0 UK: England & Wales Attribution-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-sa/2.0/uk/ http://creativecommons.org/licenses/by-sa/2.0/uk/

Site sourced from

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Pie Charts

Description

A basic introduction into the use of pie charts.

Subjects

pie | charts | pie charts | maths | numeracy | Mathematical and Computer Sciences | Computer science | I100

License

Attribution-Share Alike 2.0 UK: England & Wales Attribution-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-sa/2.0/uk/ http://creativecommons.org/licenses/by-sa/2.0/uk/

Site sourced from

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Attribution

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