Probabilidad y Estadística

Los cursos de estadística y probabilidad enseñan habilidades para comprender qué datos son significativos, incluidos la optimización, la inferencia, los ensayos y otros métodos para analizar patrones en los datos y usarlos para predecir, entender y mejorar los resultados.

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R Programming

R Programming

Johns Hopkins University
Curso
Calificado 4.5 de cinco estrellas. 19282 reseñas
Understanding Clinical Research: Behind the Statistics

Understanding Clinical Research: Behind the Statistics

University of Cape Town
Curso
Calificado 4.8 de cinco estrellas. 2077 reseñas
Understanding and Visualizing Data with Python

Understanding and Visualizing Data with Python

University of Michigan
Curso
Calificado 4.7 de cinco estrellas. 1477 reseñas
Introduction to Probability and Data with R

Introduction to Probability and Data with R

Duke University
Curso
Calificado 4.7 de cinco estrellas. 4369 reseñas
Bayesian Statistics: From Concept to Data Analysis

Bayesian Statistics: From Concept to Data Analysis

University of California, Santa Cruz
Curso
Calificado 4.6 de cinco estrellas. 2445 reseñas
Bayesian Statistics: Techniques and Models

Bayesian Statistics: Techniques and Models

University of California, Santa Cruz
Curso
Calificado 4.8 de cinco estrellas. 348 reseñas
A Crash Course in Causality:  Inferring Causal Effects from Observational Data

A Crash Course in Causality: Inferring Causal Effects from Observational Data

University of Pennsylvania
Curso
Calificado 4.7 de cinco estrellas. 271 reseñas
Econometrics: Methods and Applications

Econometrics: Methods and Applications

Erasmus University Rotterdam
Curso
Calificado 4.6 de cinco estrellas. 978 reseñas
Basic Statistics

Basic Statistics

University of Amsterdam
Curso
Calificado 4.6 de cinco estrellas. 3316 reseñas
Summary Statistics in Public Health

Summary Statistics in Public Health

Johns Hopkins University
Curso
Calificado 4.8 de cinco estrellas. 888 reseñas
Probability and Statistics: To p or not to p?

Probability and Statistics: To p or not to p?

University of London
Curso
Calificado 4.6 de cinco estrellas. 977 reseñas
Practical Time Series Analysis

Practical Time Series Analysis

The State University of New York
Curso
Calificado 4.6 de cinco estrellas. 1112 reseñas
Introduction to Statistics & Data Analysis in Public Health

Introduction to Statistics & Data Analysis in Public Health

Imperial College London
Curso
Calificado 4.7 de cinco estrellas. 704 reseñas
Improving your statistical inferences

Improving your statistical inferences

Eindhoven University of Technology
Curso
Calificado 4.9 de cinco estrellas. 606 reseñas
Getting and Cleaning Data

Getting and Cleaning Data

Johns Hopkins University
Curso
Calificado 4.6 de cinco estrellas. 7434 reseñas
Inferential Statistics

Inferential Statistics

Duke University
Curso
Calificado 4.8 de cinco estrellas. 1890 reseñas

    Preguntas frecuentes sobre Probabilidad y Estadística

  • Probability is the study of the likelihood an event will happen, and statistics is the analysis of large datasets, usually with the goal of either usefully describing this data or inferring conclusions about a larger dataset based on a representative sample. These two branches of mathematics can be considered two sides of a coin: statistics help you to understand the past, and probability helps you use that knowledge to predict the future!

    Statistics and probability are essential tools for data science. These skills enable you to determine whether your data collection methods are sound, derive relevant insights from massive datasets, build analytic models that produce usable results, and much more. Important concepts and skills in the data science context include sampling distributions, statistical significance, hypothesis testing, and regression analysis.