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Science Literacy - How Solid Science Can Help You Save the World

This course will help you become scientifically literate so that you can make better choices for yourself and the world. Unlike other courses on statistics and scientific methods, we explore global challenges - such as poverty or climate change - and then discuss how key approaches of statistics and scientific methods can help tackle these challenges. We present these approaches in a non-mathematical and easily accessible way. You will leave the course being able to recognize which efforts to do good in this world actually work, and you will have used your science literacy to make some personal changes in your life. Many current attempts to do good in this world are based on good intentions, but don’t work well, or are even harmful. In this course we talk to leading experts from academia, business and non-profit organizations about how we can use science to distinguish bad, good and even better ways of improving this world. We also invite you to change your own behavior to do more good. You will learn how to spot BS (bad science) in the media, how to evaluate whether a social program works or not, and how your career could have a better impact on this world. Finally, you will develop your own plan on how you are going to do good better with science. Guest speakers include Behavioral Economist Dan Ariely, Philosopher Peter Singer, and Happiness researcher Elizabeth Dunn.

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Rating 4.0 based on 11 ratings
Length 6 weeks
Starts Jun 17 (254 weeks ago)
Cost $49
From Erasmus University Rotterdam via Coursera
Instructors Vera Schölmerich, Kellie Liket
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science Mathematics
Tags Data Science Personal Development Probability And Statistics

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What people are saying

contents together show something

And it also provides us with simple tools to make analysis by ourselves.Space for improvement could lie in that the links between videos and reading materials of a same module or block could be strong, at least sometimes they don't seem so hooked with each other to me or I sometimes got confused what these contents together show something different from other blocks.

without taking into account

The assignment assumes one is able to produce a lecture-type of video, without taking into account that most students are not particularly good at such things (graphics, animations, video production etc.).

no division per week

It would be better if there was no division per week, but just a list of mandatory things and a list of optional things.

large gap between reality

I felt that someone was giving me the right answer for everything and I wasn't supposed to think about it all.I would rather focus my attention on the large gap between reality and "scientific" claims.

rather focus my attention

make analysis by ourselves.space

times can seem annoying

The interviews with the course's guests are definitely worth the time!The authors are trying to sound familiar and easy going, which at times can seem annoying, particularly in the beginning, when they sound as if they are talking to unknowledgeable little children.

course.the capstone project

If they would address this in the future sessions, I think many would appreciate it.The material is interesting and definitely thought-provoking, but I had trouble in seeing what is the general direction (the vector, if you will) of this course.The capstone project is also a bit too demanding, as it assumes one would create a video in which they would discuss a challenging topic.

our shared planet

In comparison to ninety percent of the other courses we all take this is so much more important over the long term for ourselves, our shared planet, and the other species we inhabit the world with.

something different from

too many peer-viewed

Too many peer-viewed assignment My feeling is that this MOOC is very inspiring in way that it brings out the fact and paradox that we previously were reluctant to say out , and that is we are not saving lives in an effective way and that's how we actually should behave if we are real egalitarians in ourselves.

appreciate it.the material

Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile.

Survey Methods Specialist $56k

Methods Chemist $67k

Methods & Procedures Analyst $77k

Methods Manufacturing Engineer $93k

Training and Methods Coordinator $98k

Junior Methods Engineer $102k

Methods Engineer 2 $116k

Senior Methods Analyst $120k

Methods and Tools $134k

Senior Methods Analysis $149k

Staff Methods Analysis $151k

Principal Methods Analysis $169k

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Rating 4.0 based on 11 ratings
Length 6 weeks
Starts Jun 17 (254 weeks ago)
Cost $49
From Erasmus University Rotterdam via Coursera
Instructors Vera Schölmerich, Kellie Liket
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science Mathematics
Tags Data Science Personal Development Probability And Statistics

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