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Learner Reviews & Feedback for Introduction to Statistics by Stanford University

4.6
stars
2,914 ratings

About the Course

Stanford's "Introduction to Statistics" teaches you statistical thinking concepts that are essential for learning from data and communicating insights. By the end of the course, you will be able to perform exploratory data analysis, understand key principles of sampling, and select appropriate tests of significance for multiple contexts. You will gain the foundational skills that prepare you to pursue more advanced topics in statistical thinking and machine learning. Topics include Descriptive Statistics, Sampling and Randomized Controlled Experiments, Probability, Sampling Distributions and the Central Limit Theorem, Regression, Common Tests of Significance, Resampling, Multiple Comparisons....

Top reviews

AB

May 23, 2023

The lectures were clear and thorough, with a good amount of examples. The quizzes were excellent, and I learned a lot from the feedback. One of the best Coursera courses I have ever taken!

BH

Jun 26, 2023

I started this course to get into machine learning and AI. This was packed with a lot of information to get you started. It doesn't got deep into each topic but great for an overal view.

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576 - 600 of 617 Reviews for Introduction to Statistics

By Jiansheng N

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Jun 22, 2021

This is not an introduction to statistics, the instructor assumes students having some basic background in probabilities, distributions. However, the slides are very useful.

By Liz G

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Dec 22, 2023

This was a difficult course to understand. I felt like there needed to be more examples and practice problems. I'm still not 100% sure how to calculate probability.

By Christopher R

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Sep 17, 2022

Extraordinarily boring videos; the professor has zero personality. Really made it hard to watch and be excited to do so.

By Aisha M M

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Nov 6, 2023

while I believe challenges are a good thing, I think the course was too much for its 'beginner' label

By Arnold C

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Jul 26, 2021

Starts off as quite beginners-level, though the onslaught of formulas can be overwhelming.

By Hong J

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Dec 11, 2022

it was ok for a general background refresh. I was expected more solid knowledge.

By Rinku D

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Mar 6, 2022

overall this is good course for learning statistics for Data science.

By Vedant G

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May 10, 2022

Content is good but pace is extremely fast towards the later weeks.

By ishita b

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Aug 21, 2022

The course was good but there is a room to make it more good

By ahmed a m n

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Feb 18, 2022

need simplification of certain topics as anova p value

By Tomasz

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Dec 21, 2021

Quite ok but some concepts are not clearly introduced.

By Ifunanya o

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Nov 5, 2021

good course but should be given a free certificate

By TJ R

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Jul 8, 2022

It was difficult at times viewing the video's.

By Mahdi F M

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Mar 25, 2023

it was a bit too complicated for my taste.

By Erdem S

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Jan 2, 2023

so technical for math focus

By Beibarys L

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Jul 24, 2021

наборы данных не актуальны

By Jaeri S

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Nov 23, 2022

needed more details!

By Tanguy N

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May 17, 2022

Very good

By Legendary W

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Feb 7, 2023

great

By Mhamed B

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Mar 13, 2023

so so

By Muaz N

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Jun 24, 2022

good

By Said

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Dec 18, 2021

It took me two lessons to figure out this course is not for me. To give you a bit of context, I'm the type of person who needs to understand a concept from the inside – to such a depth that I'd be able to explain it to anyone, no matter their age or academic ability, in plain English. True, the lectures do give you all the definitions you need and show how you can apply a certain concept in practice, but I failed to understand the why of things. And to me, that's a deal-breaker. In the beginning, I thought the problem was with me, that is I was too thick to get it, so I started YouTubing and googling stuff to try to keep up. In the end, I found myself spending more time on Google than on this course, so I decided to cut the middle man and subscribe to a couple of YouTube channels. This course isn't for me.

By Brittany R

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Mar 15, 2022

This course basically summarizes different components of statistics. The professor jumped straight into examples to explain concepts but didn't explain important terms and how he labeled parts of the equations before going into an example. I felt like there weren't explanations that would help better the understanding. I had to use outside resources to better understand what was being taught.

By Necip F E

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Apr 13, 2022

It teaches you what those tools do, but does not teach you how and why. I think this is caused by not including the calculus side of the subject. At the end of the day, you will know what those tools do, but you won't understand completely.