概率论与数理统计

概率论与数理统计课程介绍理解数据意义的技能,具体内容包括优化、推断、测验、数据模式分析方法,以及使用分析方法来预测、理解和改进结果。

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R Programming

R Programming

Johns Hopkins University
课程
评分为 4.5(满分 5 星)。19362 条评论
Understanding Clinical Research: Behind the Statistics

Understanding Clinical Research: Behind the Statistics

University of Cape Town
课程
评分为 4.8(满分 5 星)。2089 条评论
Understanding and Visualizing Data with Python

Understanding and Visualizing Data with Python

University of Michigan
课程
评分为 4.7(满分 5 星)。1497 条评论
Introduction to Probability and Data with R

Introduction to Probability and Data with R

Duke University
课程
评分为 4.7(满分 5 星)。4389 条评论
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
课程
评分为 4.7(满分 5 星)。273 条评论
Bayesian Statistics: From Concept to Data Analysis

Bayesian Statistics: From Concept to Data Analysis

University of California, Santa Cruz
课程
评分为 4.6(满分 5 星)。2458 条评论
Econometrics: Methods and Applications

Econometrics: Methods and Applications

Erasmus University Rotterdam
课程
评分为 4.6(满分 5 星)。978 条评论
统计基础

统计基础

University of Amsterdam
课程
评分为 4.6(满分 5 星)。3331 条评论
Summary Statistics in Public Health

Summary Statistics in Public Health

Johns Hopkins University
课程
评分为 4.8(满分 5 星)。903 条评论
Probability and Statistics: To p or not to p?

Probability and Statistics: To p or not to p?

University of London
课程
评分为 4.6(满分 5 星)。988 条评论
Bayesian Statistics: Techniques and Models

Bayesian Statistics: Techniques and Models

University of California, Santa Cruz
课程
评分为 4.8(满分 5 星)。355 条评论
Practical Time Series Analysis

Practical Time Series Analysis

The State University of New York
课程
评分为 4.6(满分 5 星)。1118 条评论
Introduction to Statistics & Data Analysis in Public Health

Introduction to Statistics & Data Analysis in Public Health

Imperial College London
课程
评分为 4.7(满分 5 星)。710 条评论
Improving your statistical inferences

Improving your statistical inferences

Eindhoven University of Technology
课程
评分为 4.9(满分 5 星)。609 条评论
Getting and Cleaning Data

Getting and Cleaning Data

Johns Hopkins University
课程
评分为 4.6(满分 5 星)。7451 条评论
Inferential Statistics

Inferential Statistics

Duke University
课程
评分为 4.8(满分 5 星)。1894 条评论

    关于 概率论与数理统计 的常见问题

  • 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.