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學生對 约翰霍普金斯大学 提供的 Data – What It Is, What We Can Do With It 的評價和反饋

4.5
71 個評分
17 條評論

課程概述

This course introduces students to data and statistics. By the end of the course, students should be able to interpret descriptive statistics, causal analyses and visualizations to draw meaningful insights. The course first introduces a framework for thinking about the various purposes of statistical analysis. We’ll talk about how analysts use data for descriptive, causal and predictive inference. We’ll then cover how to develop a research study for causal analysis, compute and interpret descriptive statistics and design effective visualizations. The course will help you to become a thoughtful and critical consumer of analytics. If you are in a field that increasingly relies on data-driven decision making, but you feel unequipped to interpret and evaluate data, this course will help you develop these fundamental tools of data literacy....

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1 - Data – What It Is, What We Can Do With It 的 17 個評論(共 17 個)

創建者 Cecil C L

2021年5月14日

Very well! The two courses that I studied for this Specialization have really been a good reason to continue.

The voice of Mrs. Instructor and the explanation of each topic have been effective in teaching this subject.

Only many more exercises and examples are missing to experience our applications for ourselves. I hope more practice in the updates of the courses, if they exist.

Thank you!

創建者 steve.tadeo@gmail.com

2021年3月30日

The quiz and test questions were really well thought out and required application of the knowledge presented in the course. They re-enforced the learning. The course definitely help shaped my view of Data Literacy. I like the support articles. Great sources for reference and further analysis. Thanks 100% enjoyed the class

創建者 Jason P C

2020年12月18日

I came in trying to get a better explanation of statistical concepts and I was not disappointed. This course demystifies statistics by providing clear and simple explanations. The use of relevant examples makes anyone be interested in using statistics to get a better view of the world.

創建者 Jeffrey G

2020年12月21日

This is a very well done course that does an excellent job at explaining concepts of scientific theory, basic data analysis, and visualization. These are concepts that I would absolutely use to introduce the subject to others in my organization.

創建者 Elijah

2021年5月7日

This course is truly insightful when it comes to data analysis and visualization. I have learnt so much from the course. I hope others also get to experience the kind of joy that comes with this particular course.

創建者 Nayyab A

2021年4月5日

This course explains basic statistical data analysis and research methodology in a really easy, understandable, relatable, and intuitive manner.

創建者 vignaux

2021年7月26日

Great introduction about how to understand and use Data for analysis

創建者 Alicia L Y

2021年4月6日

Excellent introductory course!

創建者 Atul P

2021年6月24日

Short and sweet.

創建者 Jenwit C

2020年12月27日

Good to start

創建者 Renee

2021年5月25日

A nice introduction. The use of the Introductory Statistics textbook was good and I've earmarked it for future reference; a couple of the blog reading choices about graph types could be updated. Looking forward to the next course in this specialization.

創建者 Eman S

2021年4月21日

An excellent introductory course for data understanding and analysis, I would advice to simplify the related readings to be more clear.

創建者 Maria S

2021年3月29日

This is a very clearly presented and well-prepared course. Some of the readings are much too advanced compared to the content of the videos and the quizzes. The course could use a little character.

創建者 KETUL S 1

2021年8月11日

i am not able to unenroll this course, so how can i do unenroll ?

創建者 Mervat M

2021年2月27日

Topics covered not properly integrated. Course seems a collection of topics from other courses, Highly dissatisfied.

Readings of week one was not very helpful.

創建者 Chandrakant B

2021年3月7日

Without my permission money has been deducted, looters

創建者 mohammad

2021年1月31日

boring and like a machine recorded text to speech