What is Bayesian Statistics, and why is it important to learn about?

Bayesian Statistics is an approach to statistics based on the work of the 18th century statistician and philosopher Thomas Bayes, and it is characterized by a rigorous mathematical attempt to quantify uncertainty. The likelihood of uncertain events is unknowable, by definition, but Bayes’s Theorem provides equations for the statistical inference of their probability based on prior information about an event - which can be updated based on the results of new data. While its origins lie hundreds of years in the past, Bayesian statistical approaches have become increasingly important in recent decades. The calculations at the heart of Bayesian statistics require intensive numerical integrations to solve, which were often infeasible before low-cost computing power became more widely accessible. But today, statisticians can evaluate integrals by running hundreds of thousands of simulation iterations with Markov chain Monte Carlo methods on an ordinary laptop computer. This new accessibility of computational power to quantify uncertainty has enabled Bayesian statistics to showcase its strength: making predictions. This capability is critical to many data science applications, and especially to the training of machine learning algorithms to create predictive analytics that assist with real-world decision-making problems. As with other areas of data science, statisticians often rely on R programming and Python programming skills to solve Bayesian equations.

What careers can I pursue with a background in Bayesian statistics?

Bayesian statistical approaches are essential to many data science and machine learning techniques, making an understanding of Bayes’ Theorem and related concepts essential to careers in these fields. If you wish to dive more deeply into the theoretical aspects of Bayesian statistics and the modeling of probability more generally, you can also pursue a career as a statistician. These experts may work in academia or the private sector, and usually have at least a master’s degree in mathematics or statistics. According to the Bureau of Labor Statistics , statisticians earn a median annual salary of $91,160.

Can I learn about Bayesian statistics by taking online courses in Coursera?

Absolutely. Coursera gives you opportunities to learn about Bayesian statistics and related concepts in data science and machine learning through courses and Specializations from top-ranked schools like Duke University, the University of California, Santa Cruz, and the National Research University Higher School of Economics in Russia. You can also learn from industry leaders like Google Cloud, or through Coursera’s own exclusive Guided Projects, which let you build skills by completing step-by-step tutorials taught by expert instructors. Regardless of your needs, the combination of high-equality education, a flexible schedule, and low tuition costs leaves no uncertainty about the value of learning about Bayesian statistics on Coursera.

What skills or experience do I need to already have before learning Bayesian statistics?

A background in statistics and certain areas of math, like algebra, can be extremely helpful when learning Bayesian statistics. This includes knowledge of and experience with statistical methods and statistical software. Any type of experience working with data, especially on a large scale, can also help. Classes, degrees, or work experience in biostatistics, psychometrics, analytics, quantitative psychology, banking, and public health can also be beneficial, especially if you plan to enter a career that centers around one of these topics or a related field. However, they aren't necessary for learning about Bayesian statistics in general.

What kind of people are best suited for roles that use Bayesian statistics?

People who aspire to work in roles that use Bayesian statistics should have analytical minds and a passion for using data to help other businesses and other people. You'll need good computer skills and a passion for statistics. You'll also need to be a good multitasker with excellent time management skills as well as someone who is highly organized. Good problem-solving skills are a must, as is flexibility. There are times when you may have total autonomy over your job and others when you're working with a team. That means you'll also need great interpersonal skills and the ability to communicate well, both verbally and in writing.

How do I know if learning Bayesian statistics is right for me?

Anyone who works with data or seeks a career working with data may be interested in learning Bayesian statistics. Many companies that seek employees to work in fields involving statistics or big data prefer someone who understands and can implement the theories of Bayesian statistics to someone who can't. These companies typically offer competitive salaries and benefits and room for career advancement. Careers that may use Bayesian statistics also tend to have a good outlook for the future. Best of all, learning about this topic can open you up to jobs in numerous industries, ranging from banking and finance to health care and biostatistics.

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University of Washington
Practical Predictive Analytics: Models and Methods
Habilidades que você terá: Basic Descriptive Statistics, Data Analysis, Data Analysis Software, Data Management, Data Visualization, Exploratory Data Analysis, General Statistics, Machine Learning, Plot (Graphics), Probability & Statistics, Statistical Analysis, Accounting, Advertising, Algebra, Business Psychology, Communication, Data Structures, Econometrics, Entrepreneurship, Marketing, Regression, Statistical Programming
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Mixed · Course · 1-4 Weeks
Arizona State University
AI and Machine Learning MasterTrack® Certificate
Habilidades que você terá: Machine Learning, Theoretical Computer Science, Software Engineering, BlockChain, Finance, Software Architecture, Algorithms, Software Testing, Statistical Machine Learning, Computer Programming, Mobile Development, Deep Learning, Data Analysis, Computational Logic, Computer Architecture, Data Visualization, Databases, Mathematics, Probability & Statistics, Computational Thinking, Data Management, General Statistics, Mathematical Theory & Analysis, Programming Principles, Bayesian Network, Computer Vision, Data Mining, Data Structures, Design and Product, Distributed Computing Architecture, Feature Engineering, NoSQL, Operating Systems, Product Design, Security Engineering, Artificial Neural Networks, Operations Research, Probability Distribution, Research and Design, Strategy and Operations, Amazon Web Services, Application Development, Calculus, Cloud Computing, Communication, Cryptography, Data Model, Database Administration, Database Application, Database Design, Dimensionality Reduction, Hardware Design, Journalism, Microarchitecture, Mobile Security, SQL, Software Framework, Statistical Programming, System Programming, iOS Development, Advertising, Algebra, Computer Graphics, Computer Networking, Critical Thinking, Docker (Software), Econometrics, Entrepreneurship, Geovisualization, Human Computer Interaction, Leadership and Management, Marketing, Matlab, Network Security, Other Programming Languages, Planning, Python Programming, Scala Programming, Security Strategy, Spreadsheet Software, Statistical Tests, Supply Chain Systems, Supply Chain and Logistics, System Security, Tableau Software, User Experience, Web Development
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Mastertrack · 6-12 Months
University of Illinois
Master of Business Administration (iMBA)
Habilidades que você terá: Accounting, Leadership and Management, Entrepreneurship, Marketing, Finance, Business Analysis, Data Analysis, Strategy and Operations, Financial Accounting, Research and Design, Strategy, Sales, Taxes, Probability & Statistics, Communication, Financial Analysis, Market Research, Business Psychology, Management Accounting, Market Analysis, Mergers & Acquisitions, Investment Management, Statistical Programming, Data Management, Digital Marketing, Human Resources, Financial Management, Audit, Generally Accepted Accounting Principles (GAAP), Design and Product, Marketing Management, General Statistics, Machine Learning, General Accounting, Python Programming, Banking, Culture, Data Visualization, Customer Analysis, Organizational Development, Corporate Accouting, Regression, Basic Descriptive Statistics, Statistical Analysis, Business Development, Budget Management, Marketing Design, Supply Chain and Logistics, Creativity, Innovation, Leadership Development, Product Marketing, Business, Business Communication, Decision Making, Exploratory Data Analysis, Project Management, R Programming, Brand Management, Media Strategy & Planning, Risk Management, Cost Accounting, Forecasting, Conflict Management, Theoretical Computer Science, Collaboration, Operations Management, Accounts Payable and Receivable, Computer Programming, Media Production, Spreadsheet Software, Advertising, Product Lifecycle, Algorithms, Contract Management, Negotiation, Product Management, Critical Thinking, Data Visualization Software, Marketing Psychology, Regulations and Compliance, Machine Learning Algorithms, Advertising Sales, Plot (Graphics), Behavioral Economics, Big Data, Data Analysis Software, Entrepreneurial Finance, Software Engineering, Statistical Tests, Storytelling, Performance Management, Business Design, Data Structures, Databases, Inventory Management, MarTech, Statistical Visualization, Adaptability, Data Mining, Human Computer Interaction, Influencing, Natural Language Processing, Product Strategy, Social Media, Software Testing, Supply Chain Systems, User Research, Change Management, Correlation And Dependence, Database Administration, Experiment, Human Learning, Mathematics, Probability Distribution, SQL, Survey Creation, Agile Software Development, Bayesian Statistics, BlockChain, Business Intelligence, Business Process Management, Extract, Transform, Load, Graph Theory, Material Handling, Network Analysis, Operations Research, People Development, People Management, Planning, Problem Solving, Public Relations, Search Engine Optimization, Securities Sales, Security Engineering, Software Security, Web Design, Web Development, Cash Management, Customer Support, Estimation, Journalism, Microsoft Excel, Packaging and Labeling, Process Analysis, Product Design, Visual Design, Visualization (Computer Graphics), Algebra, Back-End Web Development, Computer Graphics, Data Architecture, Data Model, Data Warehousing, Econometrics, Emotional Intelligence, Employee Relations, Game Theory, Operating Systems, Other Programming Languages, Product Development, Scrum (Software Development), Systems Design, Tableau Software, Virtual Reality
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Degree · 1-4 Years
University of Illinois at Urbana-Champaign
Master of Science in Accounting
Habilidades que você terá: Accounting, Leadership and Management, Entrepreneurship, Marketing, Finance, Strategy and Operations, Business Analysis, Data Analysis, Research and Design, Financial Accounting, Strategy, Sales, Taxes, Communication, Probability & Statistics, Financial Analysis, Market Research, Business Psychology, Management Accounting, Market Analysis, Mergers & Acquisitions, Investment Management, Statistical Programming, Human Resources, Data Management, Digital Marketing, Financial Management, Audit, Design and Product, Generally Accepted Accounting Principles (GAAP), Python Programming, Marketing Management, General Statistics, Machine Learning, General Accounting, Banking, Culture, Corporate Accouting, Customer Analysis, Data Visualization, Organizational Development, Basic Descriptive Statistics, Statistical Analysis, Business Development, Regression, Marketing Design, Supply Chain and Logistics, Creativity, Innovation, Leadership Development, Budget Management, Product Marketing, Business, Business Communication, Decision Making, Exploratory Data Analysis, Project Management, R Programming, Brand Management, Media Strategy & Planning, Risk Management, Conflict Management, Contract Management, Computer Programming, Cost Accounting, Forecasting, Collaboration, Operations Management, Theoretical Computer Science, Media Production, Spreadsheet Software, Accounts Payable and Receivable, Advertising, Product Lifecycle, Algorithms, Data Analysis Software, Regulations and Compliance, Negotiation, Product Management, Machine Learning Algorithms, Critical Thinking, Data Visualization Software, Marketing Psychology, Advertising Sales, Behavioral Economics, Big Data, Entrepreneurial Finance, Software Engineering, Statistical Tests, Storytelling, Plot (Graphics), Performance Management, Business Design, Correlation And Dependence, Data Structures, Databases, Inventory Management, MarTech, Statistical Visualization, Adaptability, Data Mining, Human Computer Interaction, Influencing, Natural Language Processing, Product Strategy, Social Media, Software Testing, Supply Chain Systems, User Research, Change Management, Human Learning, Survey Creation, Database Administration, Experiment, Mathematics, Probability Distribution, SQL, Agile Software Development, Bayesian Statistics, BlockChain, Business Intelligence, Business Process Management, Employee Relations, Extract, Transform, Load, Graph Theory, Material Handling, Network Analysis, Operations Research, People Development, People Management, Planning, Problem Solving, Public Relations, Search Engine Optimization, Securities Sales, Security Engineering, Software Security, Web Design, Web Development, Cash Management, Customer Support, Dimensionality Reduction, Estimation, Journalism, Machine Learning Software, Microsoft Excel, Packaging and Labeling, Process Analysis, Product Design, Statistical Machine Learning, Visual Design, Visualization (Computer Graphics), Algebra, Back-End Web Development, Computer Graphics, Data Architecture, Data Model, Data Warehousing, Econometrics, Emotional Intelligence, Game Theory, Operating Systems, Other Programming Languages, Product Development, Scientific Visualization, Scrum (Software Development), Systems Design, Tableau Software, Virtual Reality
Ganhe um diploma
Degree · 1-4 Years
Arizona State University
Software Engineering MasterTrack® Certificate
Habilidades que você terá: Machine Learning, Theoretical Computer Science, Software Engineering, BlockChain, Finance, Software Architecture, Algorithms, Software Testing, Statistical Machine Learning, Computer Programming, Mobile Development, Deep Learning, Data Analysis, Computational Logic, Computer Architecture, Data Visualization, Databases, Mathematics, Probability & Statistics, Computational Thinking, Data Management, General Statistics, Mathematical Theory & Analysis, Programming Principles, Bayesian Network, Computer Vision, Data Mining, Data Structures, Design and Product, Distributed Computing Architecture, Feature Engineering, NoSQL, Operating Systems, Product Design, Security Engineering, Artificial Neural Networks, Operations Research, Probability Distribution, Research and Design, Strategy and Operations, Amazon Web Services, Application Development, Calculus, Cloud Computing, Communication, Cryptography, Data Model, Database Administration, Database Application, Database Design, Dimensionality Reduction, Hardware Design, Journalism, Microarchitecture, Mobile Security, SQL, Software Framework, Statistical Programming, System Programming, iOS Development, Advertising, Algebra, Computer Graphics, Computer Networking, Critical Thinking, Docker (Software), Econometrics, Entrepreneurship, Geovisualization, Human Computer Interaction, Leadership and Management, Marketing, Matlab, Network Security, Other Programming Languages, Planning, Python Programming, Scala Programming, Security Strategy, Spreadsheet Software, Statistical Tests, Supply Chain Systems, Supply Chain and Logistics, System Security, Tableau Software, User Experience, Web Development
Crédito oferecido
Mastertrack · 6-12 Months
Arizona State University
Big Data MasterTrack® Certificate
Habilidades que você terá: Machine Learning, Theoretical Computer Science, Software Engineering, BlockChain, Finance, Software Architecture, Algorithms, Software Testing, Statistical Machine Learning, Computer Programming, Mobile Development, Deep Learning, Data Analysis, Computational Logic, Computer Architecture, Data Visualization, Databases, Mathematics, Probability & Statistics, Computational Thinking, Data Management, General Statistics, Mathematical Theory & Analysis, Programming Principles, Bayesian Network, Computer Vision, Data Mining, Data Structures, Design and Product, Distributed Computing Architecture, Feature Engineering, NoSQL, Operating Systems, Product Design, Security Engineering, Artificial Neural Networks, Operations Research, Probability Distribution, Research and Design, Strategy and Operations, Amazon Web Services, Application Development, Calculus, Cloud Computing, Communication, Cryptography, Data Model, Database Administration, Database Application, Database Design, Dimensionality Reduction, Hardware Design, Journalism, Microarchitecture, Mobile Security, SQL, Software Framework, Statistical Programming, System Programming, iOS Development, Advertising, Algebra, Computer Graphics, Computer Networking, Critical Thinking, Docker (Software), Econometrics, Entrepreneurship, Geovisualization, Human Computer Interaction, Leadership and Management, Marketing, Matlab, Network Security, Other Programming Languages, Planning, Python Programming, Scala Programming, Security Strategy, Spreadsheet Software, Statistical Tests, Supply Chain Systems, Supply Chain and Logistics, System Security, Tableau Software, User Experience, Web Development
Crédito oferecido
Mastertrack · 6-12 Months
Arizona State University
Cybersecurity MasterTrack® Certificate
Habilidades que você terá: Machine Learning, Theoretical Computer Science, Software Engineering, BlockChain, Finance, Software Architecture, Algorithms, Software Testing, Statistical Machine Learning, Computer Programming, Mobile Development, Deep Learning, Data Analysis, Computational Logic, Computer Architecture, Data Visualization, Databases, Mathematics, Probability & Statistics, Computational Thinking, Data Management, General Statistics, Mathematical Theory & Analysis, Programming Principles, Bayesian Network, Computer Vision, Data Mining, Data Structures, Design and Product, Distributed Computing Architecture, Feature Engineering, NoSQL, Operating Systems, Product Design, Security Engineering, Artificial Neural Networks, Operations Research, Probability Distribution, Research and Design, Strategy and Operations, Amazon Web Services, Application Development, Calculus, Cloud Computing, Communication, Cryptography, Data Model, Database Administration, Database Application, Database Design, Dimensionality Reduction, Hardware Design, Journalism, Microarchitecture, Mobile Security, SQL, Software Framework, Statistical Programming, System Programming, iOS Development, Advertising, Algebra, Computer Graphics, Computer Networking, Critical Thinking, Docker (Software), Econometrics, Entrepreneurship, Geovisualization, Human Computer Interaction, Leadership and Management, Marketing, Matlab, Network Security, Other Programming Languages, Planning, Python Programming, Scala Programming, Security Strategy, Spreadsheet Software, Statistical Tests, Supply Chain Systems, Supply Chain and Logistics, System Security, Tableau Software, User Experience, Web Development
Crédito oferecido
Mastertrack · 6-12 Months

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Em resumo, aqui estão 10 dos nossos cursos mais populares bayesian statistics

Hyperparameter Tuning with Keras Tuner: Coursera Project Network
Build Regression, Classification, and Clustering Models: CertNexus
Practical Predictive Analytics: Models and Methods: University of Washington
AI Workflow: Data Analysis and Hypothesis Testing: IBM
AI and Machine Learning MasterTrack® Certificate: Arizona State University
Master of Science in Machine Learning and Data Science: Imperial College London
Data Mining Methods: University of Colorado Boulder
Master of Business Administration (iMBA): University of Illinois
Master of Science in Accounting: University of Illinois at Urbana-Champaign
Software Engineering MasterTrack® Certificate: Arizona State University

Habilidades que você pode aprender em Probability And Statistics

Linguagem R (19)

Inferênciainferência (16)

Regressão Linear (12)

Análise Estatística (12)

Inferência Estatística (11)

Análise De Regressão (10)

Bioestatísticabioestatísticas (9)

Bayesiana (7)

Regressão Logística (7)

Distribuição De Probabilidade (7)

Estatística Bayesiana (6)

Estatísticas Médicas (6)

Perguntas frequentes sobre Estatística Bayesiana

Bayesian Statistics is an approach to statistics based on the work of the 18th century statistician and philosopher Thomas Bayes, and it is characterized by a rigorous mathematical attempt to quantify uncertainty. The likelihood of uncertain events is unknowable, by definition, but Bayes’s Theorem provides equations for the statistical inference of their probability based on prior information about an event - which can be updated based on the results of new data.
While its origins lie hundreds of years in the past, Bayesian statistical approaches have become increasingly important in recent decades. The calculations at the heart of Bayesian statistics require intensive numerical integrations to solve, which were often infeasible before low-cost computing power became more widely accessible. But today, statisticians can evaluate integrals by running hundreds of thousands of simulation iterations with Markov chain Monte Carlo methods on an ordinary laptop computer.
This new accessibility of computational power to quantify uncertainty has enabled Bayesian statistics to showcase its strength: making predictions. This capability is critical to many data science applications, and especially to the training of machine learning algorithms to create predictive analytics that assist with real-world decision-making problems. As with other areas of data science, statisticians often rely on R programming and Python programming skills to solve Bayesian equations.‎
Bayesian statistical approaches are essential to many data science and machine learning techniques, making an understanding of Bayes’ Theorem and related concepts essential to careers in these fields.
If you wish to dive more deeply into the theoretical aspects of Bayesian statistics and the modeling of probability more generally, you can also pursue a career as a statistician. These experts may work in academia or the private sector, and usually have at least a master’s degree in mathematics or statistics. According to the Bureau of Labor Statistics, statisticians earn a median annual salary of $91,160.‎
Absolutely. Coursera gives you opportunities to learn about Bayesian statistics and related concepts in data science and machine learning through courses and Specializations from top-ranked schools like Duke University, the University of California, Santa Cruz, and the National Research University Higher School of Economics in Russia. You can also learn from industry leaders like Google Cloud, or through Coursera’s own exclusive Guided Projects, which let you build skills by completing step-by-step tutorials taught by expert instructors.
Regardless of your needs, the combination of high-equality education, a flexible schedule, and low tuition costs leaves no uncertainty about the value of learning about Bayesian statistics on Coursera.‎
A background in statistics and certain areas of math, like algebra, can be extremely helpful when learning Bayesian statistics. This includes knowledge of and experience with statistical methods and statistical software. Any type of experience working with data, especially on a large scale, can also help. Classes, degrees, or work experience in biostatistics, psychometrics, analytics, quantitative psychology, banking, and public health can also be beneficial, especially if you plan to enter a career that centers around one of these topics or a related field. However, they aren't necessary for learning about Bayesian statistics in general.‎
People who aspire to work in roles that use Bayesian statistics should have analytical minds and a passion for using data to help other businesses and other people. You'll need good computer skills and a passion for statistics. You'll also need to be a good multitasker with excellent time management skills as well as someone who is highly organized. Good problem-solving skills are a must, as is flexibility. There are times when you may have total autonomy over your job and others when you're working with a team. That means you'll also need great interpersonal skills and the ability to communicate well, both verbally and in writing.‎
Anyone who works with data or seeks a career working with data may be interested in learning Bayesian statistics. Many companies that seek employees to work in fields involving statistics or big data prefer someone who understands and can implement the theories of Bayesian statistics to someone who can't. These companies typically offer competitive salaries and benefits and room for career advancement. Careers that may use Bayesian statistics also tend to have a good outlook for the future. Best of all, learning about this topic can open you up to jobs in numerous industries, ranging from banking and finance to health care and biostatistics.‎

Este conteúdo de Perguntas frequentes foi disponibilizado apenas para fins informativos. Os aprendizes são aconselhados a realizar pesquisas adicionais para garantir que os cursos e outras credenciais buscadas atendam a seus objetivos pessoais, profissionais e financeiros.