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Astrid Bernal, Mario Castillo, and Daniela Angulo

El curso está orientado a profesionales de diferentes campos, que estén interesados en adquirir conceptos fundamentales de estadística aplicada. El contenido del curso será particularmente útil para profesionales que estén interesados en adelantar estudios de postgrado en ingeniería, administración o economía, entre otras profesiones, y que requieran de una adecuada fundamentación en estadística. También será de utilidad para estudiantes universitarios que deseen reforzar o complementar su formación básica en estadística, aprovechando los diferentes recursos con los que cuenta este MOOC.

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El curso está orientado a profesionales de diferentes campos, que estén interesados en adquirir conceptos fundamentales de estadística aplicada. El contenido del curso será particularmente útil para profesionales que estén interesados en adelantar estudios de postgrado en ingeniería, administración o economía, entre otras profesiones, y que requieran de una adecuada fundamentación en estadística. También será de utilidad para estudiantes universitarios que deseen reforzar o complementar su formación básica en estadística, aprovechando los diferentes recursos con los que cuenta este MOOC.

o La estadística es un campo de la matemática aplicada que se ocupa de la recolección, descripción y análisis de datos. Actualmente, esta disciplina no es solo fundamental para el ejercicio de la ingeniería, la economía y las ciencias básicas, sino que cada vez es más importante en aspectos de la vida moderna. Múltiples artículos son publicados diariamente en periódicos y revistas a través de los cuales se pretenden explicar tendencias sociales o económicas, siendo evidente que la estadística no solo es importante para ser un buen profesional, sino también para ser un miembro de la sociedad bien informado.

o Las aplicaciones de la Estadística van desde la organización de grandes cantidades de datos, pasando por la caracterización de los clientes de una compañía o individuos de una región, hasta el diseño de campañas de mercadotecnia más eficientes, y el desarrollo de políticas sociales. Algo a lo que se atribuye el gran éxito de los japoneses en la industria de la manufactura, durante el siglo XX, es al uso de métodos estadísticos y al pensamiento estadístico del personal gerencial, lo cual permitió enfocar la atención en el análisis y uso de los datos para mejorar la calidad y eficiencia de sus procesos de fabricación.

o El curso tiene como objetivo principal que los participantes adquieran una formación sólida en los conceptos más importantes de estadística, y sus aplicaciones. En este curso haremos especial énfasis en que logres una adecuada comprensión del análisis descriptivo de datos estadísticos, así como de los métodos básicos para la estimación de parámetros poblacionales, finalizando con el entendimiento de los modelos de Regresión Lineal Simple y Múltiple, y las oportunidades de aplicación de dichos modelos.

o El curso tiene un buen balance entre el rigor en el tema y la presentación del contenido de una forma sencilla, con base en ejemplos que abordan situaciones reales simplificadas, y cuenta con videos y ejercicios orientados a facilitar la comprensión de los conceptos que se cubren en este curso.

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What's inside

Syllabus

Módulo sin título
Distribuciones muestrales y estadística descriptiva
Bienvenidos al primer módulo de este curso donde haremos una introducción al mundo de la estadística. En este módulo trataremos conceptos básicos de estadística descriptiva y de estimación de parámetros poblacionales. Al final de este módulo serás capaz de: calcular, interpretar y analizar las principales estadísticas descriptivas de un conjunto de datos; y de construir estimadores, y comprender e interpretar sus propiedades básicas y sus aplicaciones.
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Enseña conceptos esenciales de estadística para quienes desean profundizar sus conocimientos en campos técnicos o administrativos
Desarrolla habilidades analíticas y estadísticas, fortaleciendo la comprensión de datos y su aplicación en la toma de decisiones
Imparte fundamentos estadísticos esenciales para aspirantes a estudios de posgrado en ingeniería, economía y administración

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Reviews summary

Fundamentos sólidos de estadística aplicada

Según los estudiantes, este curso de Fundamentos de Estadística Aplicada de la Universidad de los Andes es una excelente base para adquirir conocimientos sólidos en la materia. Muchos elogian las explicaciones claras y didácticas del instructor y la efectividad de los ejemplos prácticos para conectar la teoría con la realidad. Aunque proporciona una fundamentación esencial para profesionales y estudiantes, algunos mencionan que el ritmo puede ser un poco rápido para quienes no tienen ninguna base previa, o que le falta mayor profundidad en temas avanzados y aplicaciones con software. Sin embargo, los comentarios recientes destacan mejoras continuas, indicando que el curso ha evolucionado positivamente.
El curso ha sido actualizado y mejorado en respuesta a la retroalimentación.
"El instructor ha mejorado muchísimo los materiales y las explicaciones son ahora incluso más claras. Se nota que han atendido las sugerencias de los estudiantes. Un curso de gran calidad y muy actual."
Proporciona una fundamentación esencial para estudios superiores y carrera.
"Este curso me ha parecido una excelente base para entender la estadística aplicada. ¡Altamente recomendado para cualquiera que busque una introducción sólida!"
"Un curso muy completo para ser introductorio. Los conceptos se explican de forma sencilla y el material de apoyo es excelente."
"Sólidos fundamentos de estadística. ... Ideal para quienes vienen de otras áreas y necesitan una base para postgrados."
"Este curso es justo lo que necesitaba para refrescar mis conocimientos. La parte de regresión lineal fue excelente."
Conecta la teoría con situaciones cotidianas y profesionales.
"Los videos son muy claros y los ejemplos son de gran ayuda. Se nota el esfuerzo del profesor por explicar temas complejos de forma sencilla."
"Los ejemplos prácticos realmente ayudan a conectar la teoría con la realidad. Me ha servido mucho para mi trabajo."
"Los conceptos se explican de forma sencilla con base en ejemplos que abordan situaciones reales simplificadas."
"El enfoque en las aplicaciones prácticas y la claridad de las explicaciones lo hacen muy valioso."
Explicaciones excepcionales hacen comprensibles conceptos complejos.
"Los videos son muy claros y los ejemplos son de gran ayuda. Se nota el esfuerzo del profesor por explicar temas complejos de forma sencilla."
"La mejor introducción a la estadística que he tomado. Las explicaciones del instructor son fantásticas, y los ejemplos prácticos realmente ayudan a conectar la teoría con la realidad."
"Sólidos fundamentos de estadística. El profesor es muy claro y didáctico."
"El instructor ha mejorado muchísimo los materiales y las explicaciones son ahora incluso más claras. Se nota que han atendido las sugerencias de los estudiantes."
Se sugiere incluir más ejercicios resueltos y guías de apoyo.
"El contenido es bueno, pero a veces me sentí un poco perdido con las fórmulas. Necesitaría más ejercicios resueltos paso a paso."
"Me ayudó a solidificar muchos conceptos. Creo que sería útil para los estudiantes sin experiencia previa si hubiera más guías o tutoriales adicionales para las matemáticas básicas subyacentes."
Puede ser básico si se buscan temas avanzados o uso de software.
"Esperaba algo más avanzado. Si ya tienes una base en estadística, este curso será muy básico para ti. No se profundiza en las aplicaciones con software y los ejemplos son muy simplificados."
"Me hubiera gustado ver más herramientas de software, pero entiendo que el enfoque es en los fundamentos."
"Tal vez un poco más de profundidad en ciertos temas sería ideal para quienes buscan ir más allá de los fundamentos."
El ritmo puede ser rápido para quienes no tienen base previa.
"Quizás para alguien sin ninguna base previa, el ritmo pueda ser un poco rápido en algunos módulos, pero con paciencia se sigue bien."
"El contenido es bueno, pero a veces me sentí un poco perdido con las fórmulas. Necesitaría más ejercicios resueltos paso a paso. Me parece que asume cierto conocimiento previo."
"Me ayudó a solidificar muchos conceptos. Creo que sería útil para los estudiantes sin experiencia previa si hubiera más guías o tutoriales adicionales para las matemáticas básicas subyacentes."
"El curso es bueno para empezar, pero me costó entender algunos temas sin ejemplos más variados. A veces sentí que se iba muy rápido."

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 Fundamentos de estadística aplicada with these activities:
Revise statistical concepts
Revising statistical concepts will help you refresh your memory and improve your understanding of the material covered in the course.
Browse courses on Statistical Concepts
Show steps
  • Review your notes from previous statistics courses.
  • Read a textbook or online resource on basic statistics.
  • Take practice quizzes or exams to test your knowledge.
Develop a cheat sheet of statistical formulas
Creating a cheat sheet of statistical formulas can help you quickly and easily access the formulas you need to solve problems.
Show steps
  • Gather a list of the statistical formulas that are covered in the course.
  • Create a cheat sheet that includes the formulas and their descriptions.
  • Use the cheat sheet to help you solve practice problems.
Watch video tutorials on statistical methods
Watching video tutorials on statistical methods can help you learn new concepts and reinforce your understanding of the material covered in the course.
Browse courses on Statistical Methods
Show steps
  • Find video tutorials on statistical methods that are relevant to the course material.
  • Watch the videos and take notes on the key concepts.
  • Try to apply the concepts you learned to real-world examples.
Two other activities
Expand to see all activities and additional details
Show all five activities
Solve practice problems
Solving practice problems can help you improve your problem-solving skills and apply the concepts you learn in the course to real-world problems.
Browse courses on Statistical Concepts
Show steps
  • Find practice problems that are relevant to the course material.
  • Solve the problems on your own.
  • Check your answers and identify any areas where you need to improve.
Apply statistical methods to a real-world problem
Applying statistical methods to a real-world problem can help you see how the concepts you learn in the course can be used to solve real-world problems.
Browse courses on Statistical Methods
Show steps
  • Identify a real-world problem that can be solved using statistical methods.
  • Collect data that is relevant to the problem.
  • Analyze the data using statistical methods.
  • Draw conclusions from the analysis.
  • Present your findings in a report or presentation.

Career center

Learners who complete Fundamentos de estadística aplicada will develop knowledge and skills that may be useful to these careers:
Risk Manager
Risk Managers use statistical methods to assess and manage risks in various industries, such as finance, insurance, and healthcare. This course can help build a foundation for this role by providing learners with a solid understanding of the fundamental concepts of statistics, including data collection, description, and analysis, as well as methods for estimating population parameters. Additionally, the emphasis on real-world examples and simplified situations will help learners develop the skills they need to understand and apply statistical methods to real-world problems, which is essential for success as a Risk Manager.
Research Analyst
Research Analysts use statistical methods to collect and analyze data in order to provide insights into various topics, such as consumer behavior, market trends, and public opinion. This course can help build a foundation for this role by providing learners with a solid understanding of the fundamental concepts of statistics, including data collection, description, and analysis, as well as methods for estimating population parameters. Additionally, the emphasis on real-world examples and simplified situations will help learners develop the skills they need to understand and apply statistical methods to real-world problems, which is essential for success as a Research Analyst.
Statistician
Statisticians use statistical methods to collect, analyze, and interpret data in order to provide insights into various fields, such as medicine, public health, and social science. This course can help build a foundation for this role by providing learners with a solid understanding of the fundamental concepts of statistics, including data collection, description, and analysis, as well as methods for estimating population parameters. Additionally, the emphasis on real-world examples and simplified situations will help learners develop the skills they need to understand and apply statistical methods to real-world problems, which is essential for success as a Statistician.
Data Analyst
Data Analysts use their knowledge of statistics and data analysis techniques to gather and interpret data in order to help businesses make informed decisions. This course can help build a foundation for this role by providing learners with a solid understanding of the fundamental concepts of statistics, including data collection, description, and analysis, as well as methods for estimating population parameters. Additionally, the emphasis on real-world examples and simplified situations will help learners develop the skills they need to understand and apply statistical methods to real-world problems, which is essential for success as a Data Analyst.
Data Scientist
Data Scientists use statistical methods and machine learning algorithms to analyze large datasets and extract valuable insights. This course can provide a solid foundation for this role by introducing learners to the fundamental concepts of statistics, including data collection, description, and analysis, as well as methods for estimating population parameters. Additionally, the emphasis on real-world examples and simplified situations will help learners develop the skills they need to understand and apply statistical methods to real-world problems, which is essential for success as a Data Scientist.
Financial Analyst
Financial Analysts use statistical methods and financial data to make informed investment decisions. This course can help build a foundation for this role by providing learners with a solid understanding of the fundamental concepts of statistics, including data collection, description, and analysis, as well as methods for estimating population parameters. Additionally, the emphasis on real-world examples and simplified situations will help learners develop the skills they need to understand and apply statistical methods to real-world problems, which is essential for success as a Financial Analyst.
Market Researcher
Market Researchers use statistical methods to collect and analyze data about consumer behavior and market trends. This course can help build a foundation for this role by providing learners with a solid understanding of the fundamental concepts of statistics, including data collection, description, and analysis, as well as methods for estimating population parameters. Additionally, the emphasis on real-world examples and simplified situations will help learners develop the skills they need to understand and apply statistical methods to real-world problems, which is essential for success as a Market Researcher.
Operations Research Analyst
Operations Research Analysts use statistical methods and optimization techniques to improve the efficiency of business operations. This course can help build a foundation for this role by providing learners with a solid understanding of the fundamental concepts of statistics, including data collection, description, and analysis, as well as methods for estimating population parameters. Additionally, the emphasis on real-world examples and simplified situations will help learners develop the skills they need to understand and apply statistical methods to real-world problems, which is essential for success as an Operations Research Analyst.
Quantitative Analyst
Quantitative Analysts use statistical methods and mathematical models to analyze financial data and make investment decisions. This course can help build a foundation for this role by providing learners with a solid understanding of the fundamental concepts of statistics, including data collection, description, and analysis, as well as methods for estimating population parameters. Additionally, the emphasis on real-world examples and simplified situations will help learners develop the skills they need to understand and apply statistical methods to real-world problems, which is essential for success as a Quantitative Analyst.
Business Analyst
Business Analysts use statistical methods and data analysis techniques to identify and solve business problems. This course can help build a foundation for this role by providing learners with a solid understanding of the fundamental concepts of statistics, including data collection, description, and analysis, as well as methods for estimating population parameters. Additionally, the emphasis on real-world examples and simplified situations will help learners develop the skills they need to understand and apply statistical methods to real-world problems, which is essential for success as a Business Analyst.
Consultant
Consultants use statistical methods and data analysis techniques to provide advice and solutions to clients in a variety of industries. This course can help build a foundation for this role by providing learners with a solid understanding of the fundamental concepts of statistics, including data collection, description, and analysis, as well as methods for estimating population parameters. Additionally, the emphasis on real-world examples and simplified situations will help learners develop the skills they need to understand and apply statistical methods to real-world problems, which is essential for success as a Consultant.
Data Engineer
Data Engineers use statistical methods and data analysis techniques to build and maintain data pipelines. This course may be helpful by providing learners with a solid understanding of the fundamental concepts of statistics, including data collection, description, and analysis, as well as methods for estimating population parameters.
Software Engineer
Software Engineers use statistical methods and data analysis techniques to design and implement software solutions. This course may be helpful by providing learners with a solid understanding of the fundamental concepts of statistics, including data collection, description, and analysis, as well as methods for estimating population parameters.
Web Developer
Web Developers use statistical methods and data analysis techniques to design and implement web applications. This course may be helpful by providing learners with a solid understanding of the fundamental concepts of statistics, including data collection, description, and analysis, as well as methods for estimating population parameters.
Machine Learning Engineer
Machine Learning Engineers use statistical methods and machine learning algorithms to build and maintain machine learning models. This course may be helpful by providing learners with a solid understanding of the fundamental concepts of statistics, including data collection, description, and analysis, as well as methods for estimating population parameters.

Reading list

We've selected nine 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 Fundamentos de estadística aplicada.
Provides a comprehensive and in-depth treatment of statistical learning methods. It covers topics such as linear regression, logistic regression, decision trees, and support vector machines, with a focus on developing a deep understanding of the underlying statistical principles and algorithms.
Provides a comprehensive and rigorous introduction to probability and statistical inference. It covers topics such as probability theory, random variables, statistical distributions, and hypothesis testing, with a focus on developing a strong foundation in the mathematical foundations of statistics.
Introduces the theory and practice of Bayesian data analysis, a powerful statistical approach that incorporates prior knowledge and uncertainty into statistical modeling. It covers topics such as Bayesian inference, model selection, and computational methods, with a focus on practical applications.
Provides a comprehensive introduction to deep learning for natural language processing. It covers topics such as neural networks, word embeddings, attention mechanisms, and transformers, with a focus on developing practical NLP applications.
Provides a comprehensive introduction to reinforcement learning, a powerful machine learning technique for solving sequential decision-making problems. It covers topics such as Markov decision processes, value functions, and policy optimization, with a focus on developing practical reinforcement learning algorithms.
Introduces the principles and applications of machine learning in business intelligence. It covers topics such as data preprocessing, feature engineering, model selection, and performance evaluation, with a focus on using machine learning algorithms to solve real-world business problems.
Este libro proporciona una introducción integral a los conceptos estadísticos básicos y sus aplicaciones. Cubre temas esenciales como la recopilación de datos, el análisis descriptivo, la inferencia estadística y la regresión.
Provides a comprehensive overview of statistical methods and their applications in business and economics. It covers topics such as data collection, descriptive statistics, inferential statistics, and regression analysis, with a focus on real-world examples.
Este libro ofrece una introducción accesible a los conceptos estadísticos para estudiantes universitarios. Proporciona una base sólida en estadística descriptiva, inferencia y regresión, haciendo hincapié en la interpretación y aplicación práctica.

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