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Introduction to Probability and Data

In this Specialization, you will learn to analyze and visualize data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, and wrangle and visualize data with R packages for data analysis.You will produce a port

4.9
495 reviews

Created by: Mine Aetinkaya-Rundel

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Overall Score : 98 / 100

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Course Description

This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The concepts and techniques in this course will serve as building blocks for the inference and modeling courses in the Specialization.
product length iconTime: 22h

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Instructor Details

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Mine Aetinkaya-Rundel is an Assistant Professor of the Practice at the Department of Statistical Science at Duke University. She received her Ph.D. in Statistics from the University of California, Los Angeles, and a B.S. in Actuarial Science from New York University's Stern School of Business. Dr. Aetinkaya-Rundel is primarily interested in innovative approaches to statistics pedagogy. Some of her recent work focuses on developing student-centered learning tools for introductory statistics courses, teaching computation at the introductory statistics level with an emphasis on reproducibility, and exploring the gender gap in self-efficacy in STEM fields. Her research interests also include spatial modeling of survey, public health, and environmental data. She is a co-author of OpenIntro Statistics and a contributing member of the OpenIntro project, whose mission is to make educational products that are open-licensed, transparent, and help lower barriers to education. She is also a co-editor of the Citizen Statistician blog and a contributor to the Taking a Chance in the Classroom column in Chance Magazine.

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Reviews

4.9

495 reviews in total

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By Tran T H on 1-Aug-19

this course is very useful to me!

By Daniel L on 30-Jul-19

It was very good, but the final project was maybe too difficult.

By Elvis S R on 29-Jul-19

An excellent introduction to both probability and the R language. Great didactics.

By Kasturi D on 17-Jul-19

Excellent course for beginners in Statistics. In depth teaching of every basic concept and its applications.

By Brahim A on 12-Jul-19

Very knowledgeable with practical use of R Studio

By Usman R M on 8-Jul-19

Excellent course!

By Lingjun K on 7-Jul-19

The Course provides a brief intro of using Python to clean and analyze data. This course is awesome for beginners who want to embark their journey in the field of Data Science.

By Wenyuan G on 27-Jun-19

A good starting course

By Cecilia L on 26-Jun-19

Mine Cetinkeya-Rundel' explains the concepts in a very very clear manner. I actually started with other statistics course on Coursera. But found it going too fast. A lot of ideas were poorly presented. I was quite frustrated with one topic, so I searched online for detail elaboration and found Mine Cetinkeya-Rundel's youtube videos. Her deliberate explanation built my confidence. Hence now I'm at her class and I really enjoy it overall.

By SABIN S on 26-Jun-19

I think the approach to learning with the basic knowledge of statistics and later it's implementation in R is really fruitful.

By Pete K on 21-Jun-19

This was a GREAT review of Stats for Me.. so glad that I found this course.

By Nicolas M on 18-Jun-19

Excellent guidance, videos and a free ebook to guide you through the process. I managed to learn alot and do well on the final project finishing the course with 95% even though I had 0 programming experience. If you are willing to spend the time studying, and reviewing the very helpful material, there is no reason whatsoever you will not be able to do well.

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Introduction to Probability and Data
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  • Video Duration: icon 22h
  • Price: Free
  • Provider: icon Coursera
  • University: icon Duke University
  • Language: icon English
  • Certificate: icon Yes

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