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
課程
評分為 4.5(滿分 5 星)。 19327 條評論
Understanding Clinical Research: Behind the Statistics

Understanding Clinical Research: Behind the Statistics

University of Cape Town
課程
評分為 4.8(滿分 5 星)。 2084 條評論
Understanding and Visualizing Data with Python

Understanding and Visualizing Data with Python

University of Michigan
課程
評分為 4.7(滿分 5 星)。 1485 條評論
Introduction to Probability and Data with R

Introduction to Probability and Data with R

Duke University
課程
評分為 4.7(滿分 5 星)。 4377 條評論
Bayesian Statistics: From Concept to Data Analysis

Bayesian Statistics: From Concept to Data Analysis

University of California, Santa Cruz
課程
評分為 4.6(滿分 5 星)。 2451 條評論
Econometrics: Methods and Applications

Econometrics: Methods and Applications

Erasmus University Rotterdam
課程
評分為 4.6(滿分 5 星)。 978 條評論
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
課程
評分為 4.7(滿分 5 星)。 273 條評論
Bayesian Statistics: Techniques and Models

Bayesian Statistics: Techniques and Models

University of California, Santa Cruz
課程
評分為 4.8(滿分 5 星)。 352 條評論
统计基础

统计基础

University of Amsterdam
課程
評分為 4.6(滿分 5 星)。 3323 條評論
Summary Statistics in Public Health

Summary Statistics in Public Health

Johns Hopkins University
課程
評分為 4.8(滿分 5 星)。 894 條評論
Practical Time Series Analysis

Practical Time Series Analysis

The State University of New York
課程
評分為 4.6(滿分 5 星)。 1115 條評論
Probability and Statistics: To p or not to p?

Probability and Statistics: To p or not to p?

University of London
課程
評分為 4.6(滿分 5 星)。 985 條評論
Introduction to Statistics & Data Analysis in Public Health

Introduction to Statistics & Data Analysis in Public Health

Imperial College London
課程
評分為 4.7(滿分 5 星)。 708 條評論
Improving your statistical inferences

Improving your statistical inferences

Eindhoven University of Technology
課程
評分為 4.9(滿分 5 星)。 607 條評論
Getting and Cleaning Data

Getting and Cleaning Data

Johns Hopkins University
課程
評分為 4.6(滿分 5 星)。 7443 條評論
An Intuitive Introduction to Probability

An Intuitive Introduction to Probability

University of Zurich
課程
評分為 4.7(滿分 5 星)。 972 條評論

    關於 概率论与数理统计 的常見問題

  • 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.