probability cheatsheet

We have hosted the application probability cheatsheet in order to run this application in our online workstations with Wine or directly.

Quick description about probability cheatsheet:

The probability_cheatsheet is a cheat sheet repository that summarizes key probability theory concepts, formulas, distributions, and properties in a concise format. It likely includes definitions of random variables, PMFs and PDFs, expectations, variance, common distributions (e.g. binomial, normal, Poisson, exponential), conditional probability, Bayes� theorem, moment generating functions, and perhaps important inequalities (Markov, Chebyshev, Chernoff). The cheat sheet is intended as a quick reference for students, data scientists, statisticians, or anyone needing to recall core probability formulas without diving into textbooks. It may include visual diagrams (e.g. distributions� shapes), tips or mnemonic notes, and examples of application (e.g. computing probabilities or expectations). Formats could include Markdown, PDF, or images for easy inclusion in study materials or slides.

Features:

• Condensed definitions and formulas for random variables, expectation, variance
• Key distributions (normal, binomial, Poisson, exponential) with their properties
• Conditional probability rules, Bayes� theorem, and independence concepts
• Important inequalities and bounds (e.g. Markov, Chebyshev)
• Visual aids or diagrams illustrating distribution shapes or relationships
• Portable formats (Markdown, PDF, image) for reference or inclusion in notes

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