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
Johns Hopkins University
R Programming
课程
Understanding Clinical Research: Behind the Statistics
University of Cape Town
Understanding Clinical Research: Behind the Statistics
课程
Understanding and Visualizing Data with Python
University of Michigan
Understanding and Visualizing Data with Python
课程
Introduction to Probability and Data with R
Duke University
Introduction to Probability and Data with R
课程
统计基础
University of Amsterdam
统计基础
课程
Probability and Statistics: To p or not to p?
University of London
Probability and Statistics: To p or not to p?
课程
Bayesian Statistics: From Concept to Data Analysis
University of California, Santa Cruz
Bayesian Statistics: From Concept to Data Analysis
课程
Summary Statistics in Public Health
Johns Hopkins University
Summary Statistics in Public Health
课程
Econometrics: Methods and Applications
Erasmus University Rotterdam
Econometrics: Methods and Applications
课程
Bayesian Statistics: Techniques and Models
University of California, Santa Cruz
Bayesian Statistics: Techniques and Models
课程
A Crash Course in Causality:  Inferring Causal Effects from Observational Data
University of Pennsylvania
A Crash Course in Causality: Inferring Causal Effects from Observational Data
课程
Introduction to Statistics & Data Analysis in Public Health
Imperial College London
Introduction to Statistics & Data Analysis in Public Health
课程
Getting and Cleaning Data
Johns Hopkins University
Getting and Cleaning Data
课程
Practical Time Series Analysis
The State University of New York
Practical Time Series Analysis
课程
Statistical Inference
Johns Hopkins University
Statistical Inference
课程
Statistical Thinking for Industrial Problem Solving, presented by JMP
SAS
Statistical Thinking for Industrial Problem Solving, presented by JMP
课程
Improving your statistical inferences
Eindhoven University of Technology
Improving your statistical inferences
课程
Inferential Statistics
Duke University
Inferential Statistics
课程
Exploratory Data Analysis
Johns Hopkins University
Exploratory Data Analysis
课程

    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.