확률과 통계

확률과 통계 강좌는 데이터의 패턴 분석 및 결과 예측, 이해 및 개선을 위해, 활용, 추정, 시험 및 기타 방법을 포함하여 데이터가 의미를 지니고 있는지의 여부를 확인할 수 있는 기술을 가르칩니다.

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Learn SQL Basics for Data Science
University of California, Davis
Learn SQL Basics for Data Science
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Methods and Statistics in Social Sciences
University of Amsterdam
Methods and Statistics in Social Sciences
SPECIALIZATION
Business Statistics and Analysis
Rice University
Business Statistics and Analysis
SPECIALIZATION
Statistics with R
Duke University
Statistics with R
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Statistics with Python
University of Michigan
Statistics with Python
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Biostatistics in Public Health
Johns Hopkins University
Biostatistics in Public Health
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Statistical Analysis with R for Public Health
Imperial College London
Statistical Analysis with R for Public Health
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Анализ данных
Novosibirsk State University
Анализ данных
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Просто о статистике (с использованием R)
Saint Petersburg State University
Просто о статистике (с использованием R)
SPECIALIZATION

    확률과 통계에 대한 자주 묻는 질문

  • 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.