이 전문 분야 정보

최근 조회 48,828

Identify interesting questions, analyze data sets, and correctly interpret results to make solid, evidence-based decisions.

This Specialization covers research methods, design and statistical analysis for social science research questions. In the final Capstone Project, you’ll apply the skills you learned by developing your own research question, gathering data, and analyzing and reporting on the results using statistical methods.

학습자 경력 결과
62%
이 특화 과정을(를) 수료한 후 새로운 경력을 시작함
14%
급여 인상 또는 승진하기
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인 강좌
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
유동적 일정
유연한 마감을 설정하고 유지 관리합니다.
초급 단계
완료하는 데 약 10개월 필요
매주 3시간 권장
영어
자막: 영어, 중국어 (간체자), 아랍어, 독일어
학습자 경력 결과
62%
이 특화 과정을(를) 수료한 후 새로운 경력을 시작함
14%
급여 인상 또는 승진하기
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인 강좌
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
유동적 일정
유연한 마감을 설정하고 유지 관리합니다.
초급 단계
완료하는 데 약 10개월 필요
매주 3시간 권장
영어
자막: 영어, 중국어 (간체자), 아랍어, 독일어

이 전문 분야에는 5개의 강좌가 있습니다.

강좌1

강좌 1

Quantitative Methods

4.7
별점
1,386개의 평가
485개의 리뷰
강좌2

강좌 2

Qualitative Research Methods

4.5
별점
764개의 평가
255개의 리뷰
강좌3

강좌 3

Basic Statistics

4.7
별점
2,972개의 평가
767개의 리뷰
강좌4

강좌 4

Inferential Statistics

4.4
별점
385개의 평가
108개의 리뷰

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자주 묻는 질문

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.

  • This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

  • This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

  • Time to completion can vary based on your schedule, but most learners are able to complete the Specialization in 10 months.

  • Each course in the Specialization is offered on demand, and may be taken at any time.

  • A basic understanding of scientific principles and research methods may be helpful, but is not required. Only very basic math skills are required, you should be able to perform: addition, subtraction, multiplication, calculation of square, square root, exponents and logarithms.

  • We recommend taking the courses in the order presented, as each subsequent course will build on material from previous courses.

  • Coursera courses and certificates don't carry university credit, though some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

  • At the end of this Specialization, you will be performing your own statistical analyses using the programming language R, with no prior knowledge of programming. Learners who complete the Research Methods and Statistics for Social Science Specialization will learn more about scientific rigor and integrity. You’ll have the methods, statistics and research skills required to complete a typical Masters program in the Social Sciences or the Johns Hopkins Data Science Specialization, and also be ready for more advanced courses on big data or multivariate statistics.

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