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Hugo Mael Hernández Trevethan

En este curso aprenderás los conceptos y aplicaciones propias de las distribuciones de probabilidad, distribuciones muestrales, estimación por intervalos y pruebas de hipótesis.

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En este curso aprenderás los conceptos y aplicaciones propias de las distribuciones de probabilidad, distribuciones muestrales, estimación por intervalos y pruebas de hipótesis.

Si ya estás familiarizado con los fundamentos de la estadística descriptiva, los datos bivariados y principios básicos de probabilidad, este curso viene a complementar perfectamente esos saberes. Si te estás adentrando por primera vez en el universo de la estadística y la probabilidad, te recomendamos ampliamente que realices el curso "estadística y probabilidad", disponible en esta misma plataforma https://www.coursera.org/learn/estadistica-probabilidad/

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What's inside

Syllabus

Modelos de probabilidad y sus aplicaciones
Estimadores e introducción a la inferencia estadística
Inferencia estadística
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Suitable para personas que tienen conocimientos previos en estadística descriptiva, datos multivariados y probabilidad básica
Complementa los conocimientos adquiridos en el curso de Estadística y Probabilidad disponible en la misma plataforma
Aborda conceptos y aplicaciones de distribuciones de probabilidad, muestrales, estimación por intervalos y pruebas de hipótesis
Instruido por Hugo Mael Hernández Trevethan, profesores reconocidos en el área de estadística

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Estadística y probabilidad: principios de Inferencia with these activities:
Resumen de conceptos clave
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Career center

Learners who complete Estadística y probabilidad: principios de Inferencia will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data analysts use their knowledge of statistics and probability to collect, clean, and analyze data. They then use this data to identify trends and patterns that can help businesses make better decisions. This course provides a solid foundation in the principles of statistics and probability, which are essential for a successful career as a data analyst.
Research Scientist
Research scientists use their knowledge of statistics and probability to design and conduct experiments, analyze data, and draw conclusions. This course provides a solid foundation in the principles of statistics and probability, which are essential for a successful career as a research scientist.
Financial Analyst
Financial analysts use their knowledge of statistics and probability to evaluate investments and make recommendations to clients. This course provides a solid foundation in the principles of statistics and probability, which are essential for a successful career as a financial analyst.
Actuary
Actuaries use their knowledge of statistics and probability to assess risk and develop insurance policies. This course provides a solid foundation in the principles of statistics and probability, which are essential for a successful career as an actuary.
Biostatistician
Biostatisticians use their knowledge of statistics and probability to design and conduct clinical trials, analyze data, and draw conclusions about the effectiveness of new drugs and treatments. This course provides a solid foundation in the principles of statistics and probability, which are essential for a successful career as a biostatistician.
Data Scientist
Data scientists use their knowledge of statistics and probability to collect, clean, and analyze data. They then use this data to develop models that can predict future events. This course provides a solid foundation in the principles of statistics and probability, which are essential for a successful career as a data scientist.
Economist
Economists use their knowledge of statistics and probability to analyze economic data and make predictions about the future of the economy. This course provides a solid foundation in the principles of statistics and probability, which are essential for a successful career as an economist.
Market Researcher
Market researchers use their knowledge of statistics and probability to conduct surveys and collect data about consumer behavior. They then use this data to help businesses make better decisions about their products and marketing campaigns. This course provides a solid foundation in the principles of statistics and probability, which are essential for a successful career as a market researcher.
Operations Research Analyst
Operations research analysts use their knowledge of statistics and probability to design and improve systems and processes. They use mathematical models to analyze data and make recommendations that can help businesses operate more efficiently. This course provides a solid foundation in the principles of statistics and probability, which are essential for a successful career as an operations research analyst.
Statistician
Statisticians use their knowledge of statistics and probability to collect, analyze, and interpret data. They use this information to help businesses and organizations make better decisions. This course provides a solid foundation in the principles of statistics and probability, which are essential for a successful career as a statistician.
Machine Learning Engineer
Machine learning engineers use their knowledge of statistics and probability to develop and implement machine learning models. These models can be used to automate tasks, make predictions, and improve decision-making. This course provides a solid foundation in the principles of statistics and probability, which are essential for a successful career as a machine learning engineer.
Data Engineer
Data engineers use their knowledge of statistics and probability to design and build data pipelines. These pipelines collect, clean, and transform data so that it can be used by data analysts and scientists. This course provides a solid foundation in the principles of statistics and probability, which are essential for a successful career as a data engineer.
Business Analyst
Business analysts use their knowledge of statistics and probability to analyze data and make recommendations that can help businesses make better decisions. This course provides a solid foundation in the principles of statistics and probability, which are essential for a successful career as a business analyst.
Risk Analyst
Risk analysts use their knowledge of statistics and probability to assess risk and develop mitigation strategies. This course provides a solid foundation in the principles of statistics and probability, which are essential for a successful career as a risk analyst.
Software Engineer
Software engineers use their knowledge of statistics and probability to develop and implement software solutions. This course provides a solid foundation in the principles of statistics and probability, which are essential for a successful career as a software engineer.

Reading list

We've selected eight books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Estadística y probabilidad: principios de Inferencia.
Este libro de texto de renombre proporciona una cobertura integral de los métodos de inferencia estadística. Es un recurso esencial para estudiantes que buscan una comprensión avanzada de estos conceptos.
Este libro proporciona una introducción integral al análisis de datos bayesiano. Es un recurso esencial para estudiantes que buscan comprender y aplicar métodos bayesianos.
Este libro proporciona una introducción rigurosa a la teoría de la probabilidad. Es un recurso valioso para estudiantes que buscan una comprensión profunda de los fundamentos de la probabilidad.
Este libro innovador explora los fundamentos de la inferencia causal. Proporciona una comprensión profunda de cómo hacer inferencias causales a partir de datos observacionales.
Este libro proporciona una introducción integral al análisis de series temporales. Es un recurso valioso para estudiantes que buscan una comprensión de los métodos de análisis de series temporales y sus aplicaciones.
Este libro proporciona una introducción al aprendizaje automático desde una perspectiva probabilística. Es un recurso valioso para estudiantes que buscan aplicar métodos estadísticos al aprendizaje automático.
Este libro proporciona una introducción práctica a la estadística y la probabilidad para ingenieros y científicos. Es un recurso valioso para estudiantes que necesitan una comprensión aplicada de estos conceptos.

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