Coursera
온라인 학위경력 찾기기업용 Coursera대학교용
  • 검색
  • 상위 강좌
  • 로그인
  • 무료 회원 가입
    Coursera
    • 검색
    • Statistics

    필터링 기준

    "statistics"에 대한 2400개의 결과

    • University of California, Santa Cruz

      University of California, Santa Cruz

      Bayesian Statistics: From Concept to Data Analysis

      획득할 기술: General Statistics, Bayesian, Statistical Programming, Inference, Bayesian Statistics, Probability Distribution, R Programming, Probability, Probability & Statistics

      4.6

      (2.9k개의 검토)

      Intermediate · Course · 1-4 Weeks

    • Imperial College London

      Imperial College London

      Epidemiology for Public Health

      획득할 기술: Bayesian Statistics, Biostatistics, Econometrics, Epidemiology, Experiment, General Statistics, Graph Theory, Mathematics, Probability & Statistics, Research and Design, Statistical Tests

      4.8

      (939개의 검토)

      Beginner · Specialization · 1-3 Months

    • 무료

      Duke University

      Duke University

      Data Science Math Skills

      획득할 기술: Mathematics, Theoretical Computer Science, Probability & Statistics, Graph Theory, Factorial, Bayesian Statistics, Computational Logic, Probability Distribution, Probability, General Statistics, Mathematical Theory & Analysis, Algebra

      4.5

      (10.2k개의 검토)

      Beginner · Course · 1-3 Months

    • IBM

      IBM

      Statistics for Data Science with Python

      획득할 기술: Data Analysis, Hypothesis, Basic Descriptive Statistics, Statistical Hypothesis Testing, Probability & Statistics, Computer Programming, General Statistics, Hypothesis Testing, Analysis, Data Visualization

      4.6

      (199개의 검토)

      Mixed · Course · 1-3 Months

    • University of Toronto

      University of Toronto

      Self-Driving Cars

      획득할 기술: Algorithms, Artificial Neural Networks, Computer Graphic Techniques, Computer Graphics, Computer Programming, Computer Vision, Decision Making, Deep Learning, Entrepreneurship, Estimation, Feature Engineering, General Statistics, Graph Theory, Leadership and Management, Linear Algebra, Machine Learning, Mathematical Theory & Analysis, Mathematics, Planning, Probability & Statistics, Probability Distribution, Python Programming, Statistical Programming, Supply Chain and Logistics, Theoretical Computer Science

      4.7

      (3k개의 검토)

      Advanced · Specialization · 3+ Months

    • IBM

      IBM

      IBM Data Science

      획득할 기술: Algebra, Algorithms, Analysis, Business Analysis, Cloud API, Cloud Computing, Communication, Computational Logic, Computer Programming, Computer Programming Tools, Correlation And Dependence, Data Analysis, Data Management, Data Mining, Data Structures, Data Visualization, Database Administration, Database Application, Databases, Econometrics, Exploratory Data Analysis, Extract, Transform, Load, General Statistics, Machine Learning, Machine Learning Algorithms, Marketing, Mathematical Theory & Analysis, Mathematics, Plot (Graphics), Probability & Statistics, Python Programming, R Programming, Regression, SPSS, SQL, Spreadsheet Software, Statistical Analysis, Statistical Machine Learning, Statistical Programming, Statistical Visualization, Theoretical Computer Science, Web

      4.6

      (91.7k개의 검토)

      Beginner · Professional Certificate · 3+ Months

    • Placeholder
      Databricks

      Databricks

      Introduction to Computational Statistics for Data Scientists

      획득할 기술: Advertising, Bayesian Statistics, Communication, General Statistics, Marketing, Probability & Statistics, Probability Distribution

      3.3

      (30개의 검토)

      Beginner · Specialization · 1-3 Months

    • Placeholder
      University of Colorado Boulder

      University of Colorado Boulder

      Statistical Modeling for Data Science Applications

      획득할 기술: Advertising, Algebra, Analysis, Communication, Econometrics, General Statistics, Machine Learning, Machine Learning Algorithms, Marketing, Mathematics, Probability & Statistics, Regression

      4.2

      (14개의 검토)

      Intermediate · Specialization · 3+ Months

    • Placeholder
      Vanderbilt University

      Vanderbilt University

      MATLAB Programming for Engineers and Scientists

      획득할 기술: Algorithms, Analysis, Computer Graphic Techniques, Computer Graphics, Computer Program, Computer Programming, Computer Programming Tools, Computer Vision, Data Analysis, Data Analysis Software, Data Visualization, General Statistics, Image Processing, Linear Algebra, Machine Learning, Mathematics, Matlab, Object-Oriented Programming, Plot (Graphics), Probability & Statistics, Programming Principles, Regression, Theoretical Computer Science

      4.8

      (16.2k개의 검토)

      Beginner · Specialization · 3+ Months

    • Placeholder
      Arizona State University

      Arizona State University

      Experimental Design Basics

      획득할 기술: Experiment, Data Analysis, Probability & Statistics, General Statistics

      4.7

      (177개의 검토)

      Intermediate · Course · 1-3 Months

    • Placeholder
      Johns Hopkins University

      Johns Hopkins University

      Statistical Inference

      획득할 기술: Experiment, Confidence, General Statistics, Hypothesis, Data Analysis, Business Analysis, Statistical Hypothesis Testing, Probability & Statistics, Statistical Analysis, Inference, Hypothesis Testing

      4.2

      (4.3k개의 검토)

      Mixed · Course · 1-4 Weeks

    • Placeholder

      무료

      University of Zurich

      University of Zurich

      An Intuitive Introduction to Probability

      획득할 기술: Machine Learning, Data Analysis, Probability, Probability & Statistics, Basic Descriptive Statistics, Chi-Squared Distribution, Bayesian Statistics, Probability Distribution, Studentized Residual, General Statistics, Bayesian Network

      4.8

      (1.3k개의 검토)

      Beginner · Course · 1-3 Months

    statistics과(와) 관련된 검색

    statistics with r
    statistics for data science
    statistics with python
    statistics for data science with python
    statistics with sas
    statistics for genomic data science
    statistics for marketing
    statistics for international business
    1234…84

    요약하자면, 여기에 가장 인기 있는 statistics 강좌 10개가 있습니다.

    • Bayesian Statistics: From Concept to Data Analysis: University of California, Santa Cruz
    • Epidemiology for Public Health: Imperial College London
    • Data Science Math Skills: Duke University
    • Statistics for Data Science with Python: IBM
    • Self-Driving Cars: University of Toronto
    • IBM Data Science: IBM
    • Introduction to Computational Statistics for Data Scientists: Databricks
    • Statistical Modeling for Data Science Applications: University of Colorado Boulder
    • MATLAB Programming for Engineers and Scientists: Vanderbilt University
    • Experimental Design Basics: Arizona State University

    통계에 대한 자주 묻는 질문

    • Statistics is the science of organizing, analyzing, and interpreting large numerical datasets, with a variety of goals. Descriptive statistics such as mean, median, mode and standard deviation summarize the characteristics of a dataset; statistical inference seeks to determine the characteristics of a large population from a representative sample through statistical hypothesis testing; and statistical regression techniques establish the correlations between an dependent variable and one or more independent variables.

      A familiarity with statistics is critically important for describing and understanding our world. From stock market volatility to political polling to the three-point percentage of your favorite basketball player, statistics help to make the complexity of the world comprehensible - and tell us what to expect. The era of big data has made the use of statistics even more necessary, and data science software like Python and R programming have made data analysis techniques more powerful and more accessible than ever.‎

    • Just as statistics have become more important for making sense of our world, an ability to understand and use statistics has become increasingly essential for a variety of careers. Whether you are working in business, government, or academia, it is increasingly expected that assertions and decisions are backed up by data. Thus, you’ll need a familiarity with statistics whether you’re an operations manager preparing a presentation on process improvements for a CEO or a policy analyst writing a research paper on criminal justice reform for a legislator.

      If you have a passion for building Markov chain models or debating the relative merits of frequentist and Bayesian statistics, you can pursue a career as a full-time statistician. According to the Bureau of Labor Statistics, statisticians earned a median annual salary of $91,160 as of May 2019, and these jobs are expected to grow much faster than average due to the demand for keen statistical analysis across all fields. Statisticians typically have at least a bachelor’s degree in mathematics, computer science, or other quantitative fields, and many positions require a master’s degree in statistics.‎

    • Yes, with absolute certainty. Coursera offers individual courses as well as Specializations in statistics, as well as courses focused on related topics such as programming in Python and R as well as the applied use of business statistics. These courses and Specializations are offered by top-ranked universities such as the University of Michigan, Duke University, and Johns Hopkins University, ensuring that you won’t sacrifice educational rigor to learn online. You can also learn about statistics through Coursera’s hands-on Guided Projects, which allow you to build skills with step-by-step tutorials from experienced instructors to help you learn with confidence.‎

    • Before starting to learn statistics, you should already have basic math skills and be able to do simple calculations. You also could take math courses in algebra or calculus to prepare for learning statistics, but many people are able to successfully complete basic statistics courses without experience using advanced math. Other skills that may be useful include analytical, problem-solving, and inferential skills. Experience working with computer programming languages can be helpful if you want to take a course to learn how to use a specific language like Python to analyze data sets.‎

    • The kind of people best suited for roles in statistics enjoy working with data and sharing their findings with others. They tend to be analytical thinkers who look for trends and patterns in the data they collect and spend time asking and answering the questions the data prompts. They're able to work with a variety of people, including team members who help them collect and analyze data and the business executives and researchers relying on the information derived from the data. People who have roles in statistics may also have strong communication and presentation skills.‎

    • If you are an analytical thinker who likes collecting, analyzing, and interpreting data, learning statistics may be right for you. Learning statistics can be a logical choice if you like to make predictions or solve problems. You may be able to use the information you learn in a statistics course as preparation for additional studies in fields like mathematics, data science, or marketing. Learning statistics may be for you if you want to work in a field where you’ll use data regularly, such as business administration, marketing, public policy, finance, or insurance. Feeling comfortable organizing information, analyzing data, and viewing it from multiple perspectives can give you an edge over your competition.‎

    이 FAQ 콘텐츠는 정보 전달 목적만으로 사용할 수 있습니다. 학습자는 과정 및 기타 학점 정보가 개인적, 직업적 및 재정적 목표에 부합하는지 확인하기 위해 추가 조사를 수행하는 것이 좋습니다.
    살펴볼 만한 다른 주제
    Placeholder
    예술 & 인문학
    338개의 강좌
    Placeholder
    비즈니스
    1095개의 강좌
    Placeholder
    컴퓨터 공학
    668개의 강좌
    Placeholder
    데이터 과학
    425개의 강좌
    Placeholder
    정보 기술
    145개의 강좌
    Placeholder
    건강
    471개의 강좌
    Placeholder
    수학 및 논리
    70개의 강좌
    Placeholder
    자기개발
    137개의 강좌
    Placeholder
    물리 과학 및 공학
    413개의 강좌
    Placeholder
    사회 과학
    401개의 강좌
    Placeholder
    언어 학습
    150개의 강좌

    Coursera Footer

    경력을 시작하거나 쌓기

    • Google 데이터 분석가
    • Google 프로젝트 관리
    • Google UX 디자인
    • Google IT 지원
    • IBM 데이터 과학
    • IBM 데이터 분석가
    • Excel & R을 사용한 IBM 데이터 분석
    • IBM 사이버 보안 분석가
    • IBM 데이터 엔지니어링
    • IBM 풀스택 클라우드 개발자
    • Facebook 소셜 미디어 마케팅
    • Facebook 마케팅 분석
    • Salesforce 영업 개발 담당자
    • Salesforce 영업 운영
    • Intuit 부기
    • Google 클라우드 자격증: 클라우드 아키텍트 취득 준비
    • Google 클라우드 자격증: 클라우드 데이터 엔지니어 취득 준비
    • 경력 시작
    • 수료증 취득 준비
    • 경력 쌓기

    인기 있는 주제 찾아보기

    • 무료 강좌
    • 언어 학습
    • 파이썬
    • Java
    • 웹 디자인
    • SQL
    • Cursos Gratis
    • Microsoft Excel
    • 프로젝트 관리
    • 사이버 보안
    • 인사
    • 데이터 과학 무료 강좌
    • 영어 말하기
    • 콘텐츠 작성
    • 풀스택 웹 개발
    • 인공 지능
    • C 프로그래밍
    • 커뮤니케이션 기술
    • 블록체인
    • 모든 강좌 보기

    인기 강좌 및 문서

    • 데이터 과학 팀을 위한 기술
    • 데이터 기반 의사 결정
    • 소프트웨어 엔지니어링 기술
    • 엔지니어링 팀을 위한 소프트 스킬
    • 경영 기술
    • 마케팅 기술
    • 영업 팀을 위한 기술
    • 제품 관리자 기술
    • 금융을 위한 기술
    • 영국에서 인기 있는 데이터 과학 강좌
    • Beliebte Technologiekurse in Deutschland
    • 인기 있는 사이버 보안 자격증
    • 인기 있는 IT 자격증
    • 인기 있는 SQL 자격증
    • 마케팅 관리자 커리어 가이드
    • 프로젝트 관리자 커리어 가이드
    • Python 프로그래밍 기술
    • 웹 개발자 커리어 가이드
    • 데이터 분석가 기술
    • UX 설계자를 위한 기술

    온라인으로 학위 또는 자격증 취득

    • MasterTrack® 자격증
    • 전문 자격증
    • 대학교 수료증
    • MBA 및 경영학 학위
    • 데이터 과학 학위
    • 컴퓨터 공학 학위
    • 데이터 분석 학위
    • 공중 보건 학위
    • 사회 과학 학위
    • 관리 학위
    • 유럽 일류 대학의 학위
    • 석사 학위
    • 학사 학위
    • 성적 기반 경로를 제공하는 학위
    • 이학사 강좌
    • 학사 학위란 무엇인가요?
    • 석사 학위를 취득하는 데 얼마나 오래 걸리나요?
    • 온라인 MBA를 들을 만한 가치가 있나요?
    • 대학원 등록금을 지불하는 7가지 방법
    • 모든 자격증 보기

    Coursera

    • 소개
    • 제공 내용
    • 리더십
    • 직업
    • 카탈로그
    • Coursera Plus
    • 전문 자격증
    • MasterTrack® 자격증
    • 학위
    • 기업용 Coursera
    • 정부용
    • 캠퍼스용
    • 파트너가 되기
    • 코로나바이러스감염증-19 대응

    커뮤니티

    • 학습자
    • 파트너
    • 개발자
    • 베타 테스터
    • 번역가
    • 블로그
    • 기술 블로그
    • 지도 센터

    기타

    • 보도 자료
    • 투자자
    • 조건
    • 개인정보 보호
    • 도움말
    • 접근성
    • 문의하기
    • 문서
    • 디렉토리
    • 계열사
    어디에서나 학습
    앱스토어에서 다운로드하기구글 플레이에서 받기
    Placeholder
    © 2022 Coursera Inc. All rights reserved.
    • Placeholder
    • Placeholder
    • Placeholder
    • Placeholder
    • Placeholder