Introduction to Probability and Data with R
Master statistical concepts and R programming through hands-on data analysis. Perfect for beginners in data science.
Master statistical concepts and R programming through hands-on data analysis. Perfect for beginners in data science.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Data Analysis with R Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.7
(5,624 ratings)
2,86,995 already enrolled
Instructors:
Mine Çetinkaya-Rundel
English
پښتو, বাংলা, اردو, 3 more
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What you'll learn
Learn to use R and RStudio for data analysis
Master sampling methods and explore data visualization
Understand basic probability theory and Bayes' rule
Apply statistical concepts to real-world datasets
Develop skills in exploratory data analysis
Skills you'll gain
This course includes:
3.7 Hours PreRecorded video
11 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 8 modules in this course
This comprehensive course introduces students to the fundamentals of probability and data analysis using R. The curriculum covers sampling methods, exploratory data analysis techniques, basic probability theory, and Bayes' rule. Students gain hands-on experience with R and RStudio through practical lab exercises and a final project. The course emphasizes both theoretical understanding and practical application, serving as a foundation for more advanced statistical inference and modeling courses.
About Introduction to Probability and Data
Module 1 · 0 Hours to complete
Introduction to Data
Module 2 · 1 Hours to complete
Introduction to Data Project
Module 3 · 1 Hours to complete
Exploratory Data Analysis and Introduction to Inference
Module 4 · 2 Hours to complete
Exploratory Data Analysis Project
Module 5 · 1 Hours to complete
Introduction to Probability
Module 6 · 2 Hours to complete
Introduction to Probability Project
Module 7 · 1 Hours to complete
Probability Distributions
Module 8 · 4 Hours to complete
Fee Structure
Instructor
Mine Çetinkaya-Rundel
4.8 rating
764 Reviews
4,02,190 Students
9 Courses
Innovator in Statistics Education and Research
Mine Çetinkaya-Rundel is an Associate Professor of the Practice in the Department of Statistical Science at Duke University. She earned her Ph.D. in Statistics from the University of California, Los Angeles, and holds a B.S. in Actuarial Science from New York University's Stern School of Business. Dr. Çetinkaya-Rundel is passionate about enhancing statistics pedagogy through innovative teaching methods. Her recent work emphasizes developing student-centered learning tools for introductory statistics courses, integrating computational skills with a focus on reproducibility, and addressing the gender gap in self-efficacy within STEM fields. Additionally, her research encompasses spatial modeling of survey, public health, and environmental data. As a co-author of "OpenIntro Statistics" and a key contributor to the OpenIntro project, she is dedicated to creating open-licensed educational resources that reduce barriers to learning. Dr. Çetinkaya-Rundel also engages with the broader statistical community as a co-editor of the Citizen Statistician blog and a contributor to the "Taking a Chance in the Classroom" column in Chance Magazine, furthering her commitment to accessible and impactful statistics education.
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4.7 course rating
5,624 ratings
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