Template:Infobox mathematics

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  1. Template:Infobox mathematics

Template:Infobox mathematics is a standardized infobox used on Wikipedia and other MediaWiki-based wikis to consistently present key information about mathematical topics. It provides a structured format for summarizing essential details about mathematical concepts, theorems, problems, mathematicians, and more. This article will serve as a comprehensive guide to understanding, using, and customizing this template, geared towards beginners.

Purpose

The primary goal of the `Infobox mathematics` template is to create a unified visual presentation across articles related to mathematics. This enhances readability and allows readers to quickly grasp the core characteristics of a given topic. Without a standardized infobox, articles can become visually inconsistent, making it harder for users to locate specific information. The template ensures that essential information like the field of mathematics, the type of object being described, associated concepts, and relevant mathematicians are readily accessible. It also aids in categorizing and linking related articles, improving the overall navigation of the wiki. A well-populated infobox immediately provides context, serving as a 'snapshot' of the mathematical subject.

How to Use the Template

The template is implemented using MediaWiki syntax and is relatively straightforward to use once you understand the parameters. Here's a breakdown of the common parameters and how to populate them. Remember that the template is case-insensitive for parameter names, but using consistent capitalization is good practice for readability.

To use the template, simply copy the following code into the beginning of your article, typically after the lead paragraph:

```wiki

  1. Template:Infobox mathematics

Template:Infobox mathematics is a standardized infobox used on Wikipedia and other MediaWiki-based wikis to consistently present key information about mathematical topics. It provides a structured format for summarizing essential details about mathematical concepts, theorems, problems, mathematicians, and more. This article will serve as a comprehensive guide to understanding, using, and customizing this template, geared towards beginners.

Purpose

The primary goal of the `Infobox mathematics` template is to create a unified visual presentation across articles related to mathematics. This enhances readability and allows readers to quickly grasp the core characteristics of a given topic. Without a standardized infobox, articles can become visually inconsistent, making it harder for users to locate specific information. The template ensures that essential information like the field of mathematics, the type of object being described, associated concepts, and relevant mathematicians are readily accessible. It also aids in categorizing and linking related articles, improving the overall navigation of the wiki. A well-populated infobox immediately provides context, serving as a 'snapshot' of the mathematical subject.

How to Use the Template

The template is implemented using MediaWiki syntax and is relatively straightforward to use once you understand the parameters. Here's a breakdown of the common parameters and how to populate them. Remember that the template is case-insensitive for parameter names, but using consistent capitalization is good practice for readability.

To use the template, simply copy the following code into the beginning of your article, typically after the lead paragraph:

```wiki Template loop detected: Template:Infobox mathematics ```

Now, let's examine each parameter in detail:

  • **`name`**: (Required) This is the name of the mathematical concept, theorem, problem, etc. This is the primary title displayed in the infobox. Example: `name = Pythagorean Theorem`
  • **`image`**: (Optional) The filename of an image to display in the infobox. The image should be relevant to the topic. Use the filename *without* the "File:" prefix. Example: `image = Pythagorean theorem.svg`
  • **`caption`**: (Optional) A caption for the image. This provides context for the image. Example: `caption = A visual representation of the Pythagorean Theorem.`
  • **`subject`**: (Optional) A more specific subject area within the field. This can further refine the categorization. Example: `subject = Euclidean geometry`
  • **`related`**: (Optional) Links to other related mathematical topics. Use wiki-linking to create these links. Multiple related topics can be listed, separated by line breaks (`
    `). Example: `related = Euclidean space
    Trigonometry
    Triangles`
  • **`mathematician`**: (Optional) The mathematician(s) associated with the topic. Links to the mathematician's Wikipedia page should be used. Multiple mathematicians can be listed, separated by line breaks. Example: `mathematician = Pythagoras
    Euclid`
  • **`year`**: (Optional) The year the topic was first discovered, formulated, or published. Example: `year = c. 570 BC` (for Pythagoras)
  • **`century`**: (Optional) The century the topic is associated with. This can be useful if the exact year is unknown. Example: `century = 6th century BC`
  • **`comments`**: (Optional) Any additional comments or notes about the topic. This is a free-text field. Example: `comments = This theorem is fundamental to many areas of mathematics and physics.`
  • **`formula`**: (Optional) A mathematical formula relevant to the topic. Use LaTeX formatting for proper rendering. Enclose the LaTeX code within `\[` and `\]`. Example: `formula = \[a^2 + b^2 = c^2\]`
  • **`links`**: (Optional) External links to relevant resources, such as MathWorld or PlanetMath. Use standard wiki link syntax. Example: `links = Pythagorean Theorem at MathWorld`

Examples

Let's illustrate with a few examples:

    • Example 1: Pythagorean Theorem**

```wiki Template loop detected: Template:Infobox mathematics ```

    • Example 2: Fermat's Last Theorem**

```wiki Template loop detected: Template:Infobox mathematics ```

Advanced Techniques and Customization

  • **Using Multiple Parameters:** Don't hesitate to use as many parameters as are relevant to the topic. A complete and informative infobox is always preferred.
  • **LaTeX Formatting:** Utilize LaTeX for mathematical formulas and equations to ensure proper rendering. Refer to LaTeX documentation for syntax details.
  • **Image Selection:** Choose images that are clear, relevant, and properly licensed. Consider using SVG images for scalability.
  • **Linking:** Always link to other relevant articles within the wiki. Good linking improves navigation and helps users explore related topics.
  • **Template Documentation:** Refer to the template's documentation page (usually a `/doc` subpage) for the most up-to-date information and advanced options. This is crucial as templates can be updated over time.
  • **Conditional Parameters:** More advanced users might explore conditional parameters to display different information based on certain conditions. This requires a deeper understanding of MediaWiki templates.
  • **CSS Styling:** While generally discouraged for beginners, advanced users can customize the appearance of the infobox using CSS. However, be mindful of maintaining consistency with the wiki's overall style.

Common Mistakes to Avoid

  • **Missing `name` parameter:** The `name` parameter is required. Without it, the infobox will not function correctly.
  • **Incorrect Image Syntax:** Ensure you are using the correct filename without the "File:" prefix.
  • **Unlinked Related Topics:** Always use wiki-linking to create links to related articles.
  • **Poor LaTeX Formatting:** Double-check your LaTeX code for errors. Incorrectly formatted LaTeX will not render properly.
  • **Overuse of `comments`:** Keep the `comments` field concise and focused on essential information.
  • **Inconsistent Parameter Usage:** Maintain consistency in how you use the parameters across different articles.

Relationship to Other Templates

The `Infobox mathematics` template is often used in conjunction with other templates, such as:

Strategies, Technical Analysis, Indicators, and Trends (Related Concepts - for broader context)

While the `Infobox mathematics` focuses on core mathematical concepts, understanding how these concepts are *applied* is crucial. Here are some areas where mathematical principles are heavily utilized:

    • Strategies:** Game Theory, Optimization Algorithms, Decision Trees, Monte Carlo Simulation, Dynamic Programming.
    • Technical Analysis:** Moving Averages, Exponential Smoothing, Fibonacci Retracements, Bollinger Bands, Relative Strength Index (RSI).
    • Indicators:** MACD (Moving Average Convergence Divergence), Stochastic Oscillator, Volume Weighted Average Price (VWAP), Average True Range (ATR), Ichimoku Cloud.
    • Trends:** Linear Regression, Time Series Analysis, Autocorrelation, Spectral Analysis, Wavelet Transform.
    • Advanced Concepts:** Fractal Geometry (Mandelbrot Set, Julia Sets), Chaos Theory (Lorenz Attractor), Neural Networks (Backpropagation), Support Vector Machines, Kalman Filtering, Bayesian Statistics.
    • Statistical Measures:** Standard Deviation, Variance, Correlation Coefficient, Regression Analysis, Hypothesis Testing.
    • Probability Distributions:** Normal Distribution, Poisson Distribution, Binomial Distribution, Exponential Distribution, Uniform Distribution.
    • Financial Modeling:** Black-Scholes Model, CAPM (Capital Asset Pricing Model), Value at Risk (VaR), Monte Carlo Simulation for Portfolio Risk.
    • Optimization:** Linear Programming, Quadratic Programming, Gradient Descent, Simulated Annealing.
    • Data Analysis:** Cluster Analysis, Principal Component Analysis (PCA), Factor Analysis, Time Series Decomposition.
    • Machine Learning:** Reinforcement Learning, Supervised Learning, Unsupervised Learning, Deep Learning, Convolutional Neural Networks (CNNs).
    • Signal Processing:** Fourier Transform, Laplace Transform, Wavelet Transform, Digital Filters.
    • Cryptography:** RSA Algorithm, AES Encryption, Hash Functions, Public-Key Cryptography.
    • Network Analysis:** Graph Theory, Centrality Measures, Community Detection, Social Network Analysis.
    • Control Theory:** PID Controllers, State-Space Representation, Feedback Control Systems.
    • Queueing Theory:** M/M/1 Queue, Little's Law, Erlang B Formula.
    • Information Theory:** Entropy, Mutual Information, Channel Capacity.
    • Numerical Analysis:** Finite Difference Method, Runge-Kutta Methods, Newton-Raphson Method.
    • Game Theory Applications:** Nash Equilibrium, Prisoner’s Dilemma, Auction Theory.
    • Time Series Forecasting:** ARIMA Models, Exponential Smoothing Methods.
    • Volatility Modeling:** GARCH Models, EWMA Models.
    • Risk Management:** Value at Risk (VaR), Expected Shortfall (ES).
    • Algorithmic Trading:** High-Frequency Trading, Automated Trading Systems.
    • Predictive Analytics:** Regression Modeling, Classification Algorithms.


This comprehensive guide should provide beginners with a solid understanding of the `Infobox mathematics` template and how to use it effectively. Remember to consult the template's documentation page for the most up-to-date information and advanced options.



Wikipedia:Infoboxes Wikipedia:Manual of Style/Infoboxes Help:Templates Help:LaTeX Mathematics Algebra Geometry Calculus Statistics Number theory

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Now, let's examine each parameter in detail:

  • **`name`**: (Required) This is the name of the mathematical concept, theorem, problem, etc. This is the primary title displayed in the infobox. Example: `name = Pythagorean Theorem`
  • **`image`**: (Optional) The filename of an image to display in the infobox. The image should be relevant to the topic. Use the filename *without* the "File:" prefix. Example: `image = Pythagorean theorem.svg`
  • **`caption`**: (Optional) A caption for the image. This provides context for the image. Example: `caption = A visual representation of the Pythagorean Theorem.`
  • **`subject`**: (Optional) A more specific subject area within the field. This can further refine the categorization. Example: `subject = Euclidean geometry`
  • **`related`**: (Optional) Links to other related mathematical topics. Use wiki-linking to create these links. Multiple related topics can be listed, separated by line breaks (`
    `). Example: `related = Euclidean space
    Trigonometry
    Triangles`
  • **`mathematician`**: (Optional) The mathematician(s) associated with the topic. Links to the mathematician's Wikipedia page should be used. Multiple mathematicians can be listed, separated by line breaks. Example: `mathematician = Pythagoras
    Euclid`
  • **`year`**: (Optional) The year the topic was first discovered, formulated, or published. Example: `year = c. 570 BC` (for Pythagoras)
  • **`century`**: (Optional) The century the topic is associated with. This can be useful if the exact year is unknown. Example: `century = 6th century BC`
  • **`comments`**: (Optional) Any additional comments or notes about the topic. This is a free-text field. Example: `comments = This theorem is fundamental to many areas of mathematics and physics.`
  • **`formula`**: (Optional) A mathematical formula relevant to the topic. Use LaTeX formatting for proper rendering. Enclose the LaTeX code within `\[` and `\]`. Example: `formula = \[a^2 + b^2 = c^2\]`
  • **`links`**: (Optional) External links to relevant resources, such as MathWorld or PlanetMath. Use standard wiki link syntax. Example: `links = Pythagorean Theorem at MathWorld`

Examples

Let's illustrate with a few examples:

    • Example 1: Pythagorean Theorem**

```wiki

  1. Template:Infobox mathematics

Template:Infobox mathematics is a standardized infobox used on Wikipedia and other MediaWiki-based wikis to consistently present key information about mathematical topics. It provides a structured format for summarizing essential details about mathematical concepts, theorems, problems, mathematicians, and more. This article will serve as a comprehensive guide to understanding, using, and customizing this template, geared towards beginners.

Purpose

The primary goal of the `Infobox mathematics` template is to create a unified visual presentation across articles related to mathematics. This enhances readability and allows readers to quickly grasp the core characteristics of a given topic. Without a standardized infobox, articles can become visually inconsistent, making it harder for users to locate specific information. The template ensures that essential information like the field of mathematics, the type of object being described, associated concepts, and relevant mathematicians are readily accessible. It also aids in categorizing and linking related articles, improving the overall navigation of the wiki. A well-populated infobox immediately provides context, serving as a 'snapshot' of the mathematical subject.

How to Use the Template

The template is implemented using MediaWiki syntax and is relatively straightforward to use once you understand the parameters. Here's a breakdown of the common parameters and how to populate them. Remember that the template is case-insensitive for parameter names, but using consistent capitalization is good practice for readability.

To use the template, simply copy the following code into the beginning of your article, typically after the lead paragraph:

```wiki Template loop detected: Template:Infobox mathematics ```

Now, let's examine each parameter in detail:

  • **`name`**: (Required) This is the name of the mathematical concept, theorem, problem, etc. This is the primary title displayed in the infobox. Example: `name = Pythagorean Theorem`
  • **`image`**: (Optional) The filename of an image to display in the infobox. The image should be relevant to the topic. Use the filename *without* the "File:" prefix. Example: `image = Pythagorean theorem.svg`
  • **`caption`**: (Optional) A caption for the image. This provides context for the image. Example: `caption = A visual representation of the Pythagorean Theorem.`
  • **`subject`**: (Optional) A more specific subject area within the field. This can further refine the categorization. Example: `subject = Euclidean geometry`
  • **`related`**: (Optional) Links to other related mathematical topics. Use wiki-linking to create these links. Multiple related topics can be listed, separated by line breaks (`
    `). Example: `related = Euclidean space
    Trigonometry
    Triangles`
  • **`mathematician`**: (Optional) The mathematician(s) associated with the topic. Links to the mathematician's Wikipedia page should be used. Multiple mathematicians can be listed, separated by line breaks. Example: `mathematician = Pythagoras
    Euclid`
  • **`year`**: (Optional) The year the topic was first discovered, formulated, or published. Example: `year = c. 570 BC` (for Pythagoras)
  • **`century`**: (Optional) The century the topic is associated with. This can be useful if the exact year is unknown. Example: `century = 6th century BC`
  • **`comments`**: (Optional) Any additional comments or notes about the topic. This is a free-text field. Example: `comments = This theorem is fundamental to many areas of mathematics and physics.`
  • **`formula`**: (Optional) A mathematical formula relevant to the topic. Use LaTeX formatting for proper rendering. Enclose the LaTeX code within `\[` and `\]`. Example: `formula = \[a^2 + b^2 = c^2\]`
  • **`links`**: (Optional) External links to relevant resources, such as MathWorld or PlanetMath. Use standard wiki link syntax. Example: `links = Pythagorean Theorem at MathWorld`

Examples

Let's illustrate with a few examples:

    • Example 1: Pythagorean Theorem**

```wiki Template loop detected: Template:Infobox mathematics ```

    • Example 2: Fermat's Last Theorem**

```wiki Template loop detected: Template:Infobox mathematics ```

Advanced Techniques and Customization

  • **Using Multiple Parameters:** Don't hesitate to use as many parameters as are relevant to the topic. A complete and informative infobox is always preferred.
  • **LaTeX Formatting:** Utilize LaTeX for mathematical formulas and equations to ensure proper rendering. Refer to LaTeX documentation for syntax details.
  • **Image Selection:** Choose images that are clear, relevant, and properly licensed. Consider using SVG images for scalability.
  • **Linking:** Always link to other relevant articles within the wiki. Good linking improves navigation and helps users explore related topics.
  • **Template Documentation:** Refer to the template's documentation page (usually a `/doc` subpage) for the most up-to-date information and advanced options. This is crucial as templates can be updated over time.
  • **Conditional Parameters:** More advanced users might explore conditional parameters to display different information based on certain conditions. This requires a deeper understanding of MediaWiki templates.
  • **CSS Styling:** While generally discouraged for beginners, advanced users can customize the appearance of the infobox using CSS. However, be mindful of maintaining consistency with the wiki's overall style.

Common Mistakes to Avoid

  • **Missing `name` parameter:** The `name` parameter is required. Without it, the infobox will not function correctly.
  • **Incorrect Image Syntax:** Ensure you are using the correct filename without the "File:" prefix.
  • **Unlinked Related Topics:** Always use wiki-linking to create links to related articles.
  • **Poor LaTeX Formatting:** Double-check your LaTeX code for errors. Incorrectly formatted LaTeX will not render properly.
  • **Overuse of `comments`:** Keep the `comments` field concise and focused on essential information.
  • **Inconsistent Parameter Usage:** Maintain consistency in how you use the parameters across different articles.

Relationship to Other Templates

The `Infobox mathematics` template is often used in conjunction with other templates, such as:

Strategies, Technical Analysis, Indicators, and Trends (Related Concepts - for broader context)

While the `Infobox mathematics` focuses on core mathematical concepts, understanding how these concepts are *applied* is crucial. Here are some areas where mathematical principles are heavily utilized:

    • Strategies:** Game Theory, Optimization Algorithms, Decision Trees, Monte Carlo Simulation, Dynamic Programming.
    • Technical Analysis:** Moving Averages, Exponential Smoothing, Fibonacci Retracements, Bollinger Bands, Relative Strength Index (RSI).
    • Indicators:** MACD (Moving Average Convergence Divergence), Stochastic Oscillator, Volume Weighted Average Price (VWAP), Average True Range (ATR), Ichimoku Cloud.
    • Trends:** Linear Regression, Time Series Analysis, Autocorrelation, Spectral Analysis, Wavelet Transform.
    • Advanced Concepts:** Fractal Geometry (Mandelbrot Set, Julia Sets), Chaos Theory (Lorenz Attractor), Neural Networks (Backpropagation), Support Vector Machines, Kalman Filtering, Bayesian Statistics.
    • Statistical Measures:** Standard Deviation, Variance, Correlation Coefficient, Regression Analysis, Hypothesis Testing.
    • Probability Distributions:** Normal Distribution, Poisson Distribution, Binomial Distribution, Exponential Distribution, Uniform Distribution.
    • Financial Modeling:** Black-Scholes Model, CAPM (Capital Asset Pricing Model), Value at Risk (VaR), Monte Carlo Simulation for Portfolio Risk.
    • Optimization:** Linear Programming, Quadratic Programming, Gradient Descent, Simulated Annealing.
    • Data Analysis:** Cluster Analysis, Principal Component Analysis (PCA), Factor Analysis, Time Series Decomposition.
    • Machine Learning:** Reinforcement Learning, Supervised Learning, Unsupervised Learning, Deep Learning, Convolutional Neural Networks (CNNs).
    • Signal Processing:** Fourier Transform, Laplace Transform, Wavelet Transform, Digital Filters.
    • Cryptography:** RSA Algorithm, AES Encryption, Hash Functions, Public-Key Cryptography.
    • Network Analysis:** Graph Theory, Centrality Measures, Community Detection, Social Network Analysis.
    • Control Theory:** PID Controllers, State-Space Representation, Feedback Control Systems.
    • Queueing Theory:** M/M/1 Queue, Little's Law, Erlang B Formula.
    • Information Theory:** Entropy, Mutual Information, Channel Capacity.
    • Numerical Analysis:** Finite Difference Method, Runge-Kutta Methods, Newton-Raphson Method.
    • Game Theory Applications:** Nash Equilibrium, Prisoner’s Dilemma, Auction Theory.
    • Time Series Forecasting:** ARIMA Models, Exponential Smoothing Methods.
    • Volatility Modeling:** GARCH Models, EWMA Models.
    • Risk Management:** Value at Risk (VaR), Expected Shortfall (ES).
    • Algorithmic Trading:** High-Frequency Trading, Automated Trading Systems.
    • Predictive Analytics:** Regression Modeling, Classification Algorithms.


This comprehensive guide should provide beginners with a solid understanding of the `Infobox mathematics` template and how to use it effectively. Remember to consult the template's documentation page for the most up-to-date information and advanced options.



Wikipedia:Infoboxes Wikipedia:Manual of Style/Infoboxes Help:Templates Help:LaTeX Mathematics Algebra Geometry Calculus Statistics Number theory

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    • Example 2: Fermat's Last Theorem**

```wiki

  1. Template:Infobox mathematics

Template:Infobox mathematics is a standardized infobox used on Wikipedia and other MediaWiki-based wikis to consistently present key information about mathematical topics. It provides a structured format for summarizing essential details about mathematical concepts, theorems, problems, mathematicians, and more. This article will serve as a comprehensive guide to understanding, using, and customizing this template, geared towards beginners.

Purpose

The primary goal of the `Infobox mathematics` template is to create a unified visual presentation across articles related to mathematics. This enhances readability and allows readers to quickly grasp the core characteristics of a given topic. Without a standardized infobox, articles can become visually inconsistent, making it harder for users to locate specific information. The template ensures that essential information like the field of mathematics, the type of object being described, associated concepts, and relevant mathematicians are readily accessible. It also aids in categorizing and linking related articles, improving the overall navigation of the wiki. A well-populated infobox immediately provides context, serving as a 'snapshot' of the mathematical subject.

How to Use the Template

The template is implemented using MediaWiki syntax and is relatively straightforward to use once you understand the parameters. Here's a breakdown of the common parameters and how to populate them. Remember that the template is case-insensitive for parameter names, but using consistent capitalization is good practice for readability.

To use the template, simply copy the following code into the beginning of your article, typically after the lead paragraph:

```wiki Template loop detected: Template:Infobox mathematics ```

Now, let's examine each parameter in detail:

  • **`name`**: (Required) This is the name of the mathematical concept, theorem, problem, etc. This is the primary title displayed in the infobox. Example: `name = Pythagorean Theorem`
  • **`image`**: (Optional) The filename of an image to display in the infobox. The image should be relevant to the topic. Use the filename *without* the "File:" prefix. Example: `image = Pythagorean theorem.svg`
  • **`caption`**: (Optional) A caption for the image. This provides context for the image. Example: `caption = A visual representation of the Pythagorean Theorem.`
  • **`subject`**: (Optional) A more specific subject area within the field. This can further refine the categorization. Example: `subject = Euclidean geometry`
  • **`related`**: (Optional) Links to other related mathematical topics. Use wiki-linking to create these links. Multiple related topics can be listed, separated by line breaks (`
    `). Example: `related = Euclidean space
    Trigonometry
    Triangles`
  • **`mathematician`**: (Optional) The mathematician(s) associated with the topic. Links to the mathematician's Wikipedia page should be used. Multiple mathematicians can be listed, separated by line breaks. Example: `mathematician = Pythagoras
    Euclid`
  • **`year`**: (Optional) The year the topic was first discovered, formulated, or published. Example: `year = c. 570 BC` (for Pythagoras)
  • **`century`**: (Optional) The century the topic is associated with. This can be useful if the exact year is unknown. Example: `century = 6th century BC`
  • **`comments`**: (Optional) Any additional comments or notes about the topic. This is a free-text field. Example: `comments = This theorem is fundamental to many areas of mathematics and physics.`
  • **`formula`**: (Optional) A mathematical formula relevant to the topic. Use LaTeX formatting for proper rendering. Enclose the LaTeX code within `\[` and `\]`. Example: `formula = \[a^2 + b^2 = c^2\]`
  • **`links`**: (Optional) External links to relevant resources, such as MathWorld or PlanetMath. Use standard wiki link syntax. Example: `links = Pythagorean Theorem at MathWorld`

Examples

Let's illustrate with a few examples:

    • Example 1: Pythagorean Theorem**

```wiki Template loop detected: Template:Infobox mathematics ```

    • Example 2: Fermat's Last Theorem**

```wiki Template loop detected: Template:Infobox mathematics ```

Advanced Techniques and Customization

  • **Using Multiple Parameters:** Don't hesitate to use as many parameters as are relevant to the topic. A complete and informative infobox is always preferred.
  • **LaTeX Formatting:** Utilize LaTeX for mathematical formulas and equations to ensure proper rendering. Refer to LaTeX documentation for syntax details.
  • **Image Selection:** Choose images that are clear, relevant, and properly licensed. Consider using SVG images for scalability.
  • **Linking:** Always link to other relevant articles within the wiki. Good linking improves navigation and helps users explore related topics.
  • **Template Documentation:** Refer to the template's documentation page (usually a `/doc` subpage) for the most up-to-date information and advanced options. This is crucial as templates can be updated over time.
  • **Conditional Parameters:** More advanced users might explore conditional parameters to display different information based on certain conditions. This requires a deeper understanding of MediaWiki templates.
  • **CSS Styling:** While generally discouraged for beginners, advanced users can customize the appearance of the infobox using CSS. However, be mindful of maintaining consistency with the wiki's overall style.

Common Mistakes to Avoid

  • **Missing `name` parameter:** The `name` parameter is required. Without it, the infobox will not function correctly.
  • **Incorrect Image Syntax:** Ensure you are using the correct filename without the "File:" prefix.
  • **Unlinked Related Topics:** Always use wiki-linking to create links to related articles.
  • **Poor LaTeX Formatting:** Double-check your LaTeX code for errors. Incorrectly formatted LaTeX will not render properly.
  • **Overuse of `comments`:** Keep the `comments` field concise and focused on essential information.
  • **Inconsistent Parameter Usage:** Maintain consistency in how you use the parameters across different articles.

Relationship to Other Templates

The `Infobox mathematics` template is often used in conjunction with other templates, such as:

Strategies, Technical Analysis, Indicators, and Trends (Related Concepts - for broader context)

While the `Infobox mathematics` focuses on core mathematical concepts, understanding how these concepts are *applied* is crucial. Here are some areas where mathematical principles are heavily utilized:

    • Strategies:** Game Theory, Optimization Algorithms, Decision Trees, Monte Carlo Simulation, Dynamic Programming.
    • Technical Analysis:** Moving Averages, Exponential Smoothing, Fibonacci Retracements, Bollinger Bands, Relative Strength Index (RSI).
    • Indicators:** MACD (Moving Average Convergence Divergence), Stochastic Oscillator, Volume Weighted Average Price (VWAP), Average True Range (ATR), Ichimoku Cloud.
    • Trends:** Linear Regression, Time Series Analysis, Autocorrelation, Spectral Analysis, Wavelet Transform.
    • Advanced Concepts:** Fractal Geometry (Mandelbrot Set, Julia Sets), Chaos Theory (Lorenz Attractor), Neural Networks (Backpropagation), Support Vector Machines, Kalman Filtering, Bayesian Statistics.
    • Statistical Measures:** Standard Deviation, Variance, Correlation Coefficient, Regression Analysis, Hypothesis Testing.
    • Probability Distributions:** Normal Distribution, Poisson Distribution, Binomial Distribution, Exponential Distribution, Uniform Distribution.
    • Financial Modeling:** Black-Scholes Model, CAPM (Capital Asset Pricing Model), Value at Risk (VaR), Monte Carlo Simulation for Portfolio Risk.
    • Optimization:** Linear Programming, Quadratic Programming, Gradient Descent, Simulated Annealing.
    • Data Analysis:** Cluster Analysis, Principal Component Analysis (PCA), Factor Analysis, Time Series Decomposition.
    • Machine Learning:** Reinforcement Learning, Supervised Learning, Unsupervised Learning, Deep Learning, Convolutional Neural Networks (CNNs).
    • Signal Processing:** Fourier Transform, Laplace Transform, Wavelet Transform, Digital Filters.
    • Cryptography:** RSA Algorithm, AES Encryption, Hash Functions, Public-Key Cryptography.
    • Network Analysis:** Graph Theory, Centrality Measures, Community Detection, Social Network Analysis.
    • Control Theory:** PID Controllers, State-Space Representation, Feedback Control Systems.
    • Queueing Theory:** M/M/1 Queue, Little's Law, Erlang B Formula.
    • Information Theory:** Entropy, Mutual Information, Channel Capacity.
    • Numerical Analysis:** Finite Difference Method, Runge-Kutta Methods, Newton-Raphson Method.
    • Game Theory Applications:** Nash Equilibrium, Prisoner’s Dilemma, Auction Theory.
    • Time Series Forecasting:** ARIMA Models, Exponential Smoothing Methods.
    • Volatility Modeling:** GARCH Models, EWMA Models.
    • Risk Management:** Value at Risk (VaR), Expected Shortfall (ES).
    • Algorithmic Trading:** High-Frequency Trading, Automated Trading Systems.
    • Predictive Analytics:** Regression Modeling, Classification Algorithms.


This comprehensive guide should provide beginners with a solid understanding of the `Infobox mathematics` template and how to use it effectively. Remember to consult the template's documentation page for the most up-to-date information and advanced options.



Wikipedia:Infoboxes Wikipedia:Manual of Style/Infoboxes Help:Templates Help:LaTeX Mathematics Algebra Geometry Calculus Statistics Number theory

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Advanced Techniques and Customization

  • **Using Multiple Parameters:** Don't hesitate to use as many parameters as are relevant to the topic. A complete and informative infobox is always preferred.
  • **LaTeX Formatting:** Utilize LaTeX for mathematical formulas and equations to ensure proper rendering. Refer to LaTeX documentation for syntax details.
  • **Image Selection:** Choose images that are clear, relevant, and properly licensed. Consider using SVG images for scalability.
  • **Linking:** Always link to other relevant articles within the wiki. Good linking improves navigation and helps users explore related topics.
  • **Template Documentation:** Refer to the template's documentation page (usually a `/doc` subpage) for the most up-to-date information and advanced options. This is crucial as templates can be updated over time.
  • **Conditional Parameters:** More advanced users might explore conditional parameters to display different information based on certain conditions. This requires a deeper understanding of MediaWiki templates.
  • **CSS Styling:** While generally discouraged for beginners, advanced users can customize the appearance of the infobox using CSS. However, be mindful of maintaining consistency with the wiki's overall style.

Common Mistakes to Avoid

  • **Missing `name` parameter:** The `name` parameter is required. Without it, the infobox will not function correctly.
  • **Incorrect Image Syntax:** Ensure you are using the correct filename without the "File:" prefix.
  • **Unlinked Related Topics:** Always use wiki-linking to create links to related articles.
  • **Poor LaTeX Formatting:** Double-check your LaTeX code for errors. Incorrectly formatted LaTeX will not render properly.
  • **Overuse of `comments`:** Keep the `comments` field concise and focused on essential information.
  • **Inconsistent Parameter Usage:** Maintain consistency in how you use the parameters across different articles.

Relationship to Other Templates

The `Infobox mathematics` template is often used in conjunction with other templates, such as:

Strategies, Technical Analysis, Indicators, and Trends (Related Concepts - for broader context)

While the `Infobox mathematics` focuses on core mathematical concepts, understanding how these concepts are *applied* is crucial. Here are some areas where mathematical principles are heavily utilized:

    • Strategies:** Game Theory, Optimization Algorithms, Decision Trees, Monte Carlo Simulation, Dynamic Programming.
    • Technical Analysis:** Moving Averages, Exponential Smoothing, Fibonacci Retracements, Bollinger Bands, Relative Strength Index (RSI).
    • Indicators:** MACD (Moving Average Convergence Divergence), Stochastic Oscillator, Volume Weighted Average Price (VWAP), Average True Range (ATR), Ichimoku Cloud.
    • Trends:** Linear Regression, Time Series Analysis, Autocorrelation, Spectral Analysis, Wavelet Transform.
    • Advanced Concepts:** Fractal Geometry (Mandelbrot Set, Julia Sets), Chaos Theory (Lorenz Attractor), Neural Networks (Backpropagation), Support Vector Machines, Kalman Filtering, Bayesian Statistics.
    • Statistical Measures:** Standard Deviation, Variance, Correlation Coefficient, Regression Analysis, Hypothesis Testing.
    • Probability Distributions:** Normal Distribution, Poisson Distribution, Binomial Distribution, Exponential Distribution, Uniform Distribution.
    • Financial Modeling:** Black-Scholes Model, CAPM (Capital Asset Pricing Model), Value at Risk (VaR), Monte Carlo Simulation for Portfolio Risk.
    • Optimization:** Linear Programming, Quadratic Programming, Gradient Descent, Simulated Annealing.
    • Data Analysis:** Cluster Analysis, Principal Component Analysis (PCA), Factor Analysis, Time Series Decomposition.
    • Machine Learning:** Reinforcement Learning, Supervised Learning, Unsupervised Learning, Deep Learning, Convolutional Neural Networks (CNNs).
    • Signal Processing:** Fourier Transform, Laplace Transform, Wavelet Transform, Digital Filters.
    • Cryptography:** RSA Algorithm, AES Encryption, Hash Functions, Public-Key Cryptography.
    • Network Analysis:** Graph Theory, Centrality Measures, Community Detection, Social Network Analysis.
    • Control Theory:** PID Controllers, State-Space Representation, Feedback Control Systems.
    • Queueing Theory:** M/M/1 Queue, Little's Law, Erlang B Formula.
    • Information Theory:** Entropy, Mutual Information, Channel Capacity.
    • Numerical Analysis:** Finite Difference Method, Runge-Kutta Methods, Newton-Raphson Method.
    • Game Theory Applications:** Nash Equilibrium, Prisoner’s Dilemma, Auction Theory.
    • Time Series Forecasting:** ARIMA Models, Exponential Smoothing Methods.
    • Volatility Modeling:** GARCH Models, EWMA Models.
    • Risk Management:** Value at Risk (VaR), Expected Shortfall (ES).
    • Algorithmic Trading:** High-Frequency Trading, Automated Trading Systems.
    • Predictive Analytics:** Regression Modeling, Classification Algorithms.


This comprehensive guide should provide beginners with a solid understanding of the `Infobox mathematics` template and how to use it effectively. Remember to consult the template's documentation page for the most up-to-date information and advanced options.



Wikipedia:Infoboxes Wikipedia:Manual of Style/Infoboxes Help:Templates Help:LaTeX Mathematics Algebra Geometry Calculus Statistics Number theory

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