Fundamentos de estadística aplicada from Coursera

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.

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.

Intervalos de confianza

En este módulo nos ocuparemos de estudiar la construcción, análisis e interpretación de los intervalos de confianza de uso más común en las aplicaciones. Al final de este módulo serás capaz de: construir, calcular e interpretar intervalos de confianza

Pruebas de Hipótesis

En este módulo nos ocuparemos de estudiar las definiciones de hipótesis nula e hipótesis alterna, prueba estadística y región crítica, errores tipo I y tipo II, así como la construcción de pruebas de hipótesis de uso más común en las aplicaciones. Al final de este módulo serás capaz de: identificar, formular y evaluar las pruebas de hipótesis estadísticas de mayor aplicación.

Regresión Lineal

En este módulo nos ocuparemos de la formulación de modelos de regresión lineal simple y múltiple, así como el análisis e interpretación de sus resultados. Al final de este módulo serás capaz de: construir modelos de regresión lineal simple y múltiple, interpretar sus resultados y verificar sus supuestos.

Good to know

Know what's good

, what to watch for

, 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

Reviews summary

Well-received applied statistics course

This course provides a solid foundation in fundamental statistics principles and their application. It particularly emphasizes understanding descriptive data analysis, basic methods for estimating population parameters, and linear regression modeling. The course is well-balanced between theory and practical examples using simplified real-life situations, supported by videos and exercises. It received positive feedback from students who appreciated its comprehensive content, clarity, and practical approach.

Covers all the essential topics of descriptive and inferential statistics.

"Buen curso, cubre lo mas importante en modelos estadisticos y te da el conocimiento necesario para prepararte para examenes de esta area del conocimiento"

Content is presented in an easy-to-understand manner, with real-life examples.

"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..."

Concepts are explained clearly, with well-paced lectures and examples.

"Muy buen curso. La explicación de los conceptos es clara y se proporcionan ejemplos para comprenderlos mejor."

Emphasizes practical applications, making the concepts relatable.

"Excelente y practica la manera de enseñar los temas de los fundamentos de la estadistica aplicada."

Students mentioned a lack of exercises, particularly in the final unit.

"Aprendí! sí, eso no es cuestionable y se agradece. Sin embargo, hubo muy pocos ejercicios en la última unidad..."

Some students expressed difficulty accessing related tables and software.

"Nunca encontré las tablas que ellos explicaban en las lecciones."

"Se implementó un software licenciado el cual no se utilizó..."

Career center

Learners who complete Fundamentos de estadística aplicada will develop knowledge and skills that may be useful to these careers:

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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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