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Learner Reviews & Feedback for Statistical Inference by Johns Hopkins University

4.2
stars
4,423 ratings

About the Course

Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. Furthermore, there are broad theories (frequentists, Bayesian, likelihood, design based, …) and numerous complexities (missing data, observed and unobserved confounding, biases) for performing inference. A practitioner can often be left in a debilitating maze of techniques, philosophies and nuance. This course presents the fundamentals of inference in a practical approach for getting things done. After taking this course, students will understand the broad directions of statistical inference and use this information for making informed choices in analyzing data....

Top reviews

JA

Oct 25, 2018

Course is compressed with lots of statistical concepts. Which is very good as most must know concepts are imparted. Lots of extra reading is required to gain all insights. Very good motivating start .

RI

Sep 24, 2020

the teachers were awesome in this course. I liked this course a lot.Understood it properly.Thanks to all the beloved teachers and mentors who toiled hard to make these course easy to handle.Gracious!

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676 - 700 of 869 Reviews for Statistical Inference

By Asier

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Mar 10, 2016

At times the content can be confusing. Some points are clearly explained. "Data Analysys Tools" course is a good complement in order to understand the subject.

By Talant R

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Aug 26, 2016

Covers a lot of info too fast! Some concepts are not clearly explained , had to surf online to get better understanding. Overall, fine course, very practical.

By Yadder A

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Jan 25, 2018

I didn't like the way how the professor explained the topics. It was difficult to understand him. I just understood when I did the swirl activities.

By Diego T B

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Dec 4, 2017

Very useful but too many concepts. It was hard to follow him during 20 minutes. Videos are very extensive, also useful. But take into account this.

By Dhaval S

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Feb 21, 2017

Indept videos and materials should be provided for this course. The lectures are not enough to understand the Statistics involved in data science.

By Chouaib N

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Nov 11, 2019

The course content is very interesting and sums up fundamental aspects of statistical inference. But the way the course is presented is average.

By Aaron S

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May 7, 2018

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ts just to have a chance of passing this one.

By Mohammed A E M

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Jul 17, 2017

the subject kinda not hard but not easy to understand also, how ever the instractor was kinda fast which made me lake some of the information.

By Ivan G

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Jan 7, 2017

To be honest, I like the subject but found the course material and content not very well structured. I missed more mathematical foundation.

By Deleted A

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Dec 3, 2016

Brian Caffo is explaining the Statistical Inference methodically, but he could work on making the lectures less tiresome and monotonous.

By Ramon S

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May 19, 2017

Not really a logical path to follow. Too much topics for me. I really needed more examples with code.

Thanks a lot for the lessons!

By Naeem K

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Aug 8, 2016

The amount of materials is more than course period. You may need to study a couple of other resources to understand the course.

By Hernan S

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Apr 15, 2016

The subject is interesting, but the explanations are a little confusing. May need more diverse real-life examples to relate.

By Masahiro H

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Mar 27, 2016

it gives an idea of how one is prepared to ingress to Data Science. I

see that I need to review it more carefully later on.

By Stavros S

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Nov 21, 2019

Weeks 3 and 4 should have been split into 2 extra weeks to explain the concepts deeper and also have more exercises

By Marcus H Y T

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Jun 1, 2019

Concepts are not well explained and slides are not well prepared. Last few topics are too brief to be useful.

By Maria C S

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May 1, 2019

3 stars because a total beginner would not have been able to follow these lessons without a lot of rewinding.

By Joe F

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Nov 27, 2016

Materials need to be updated - there are way too many inconsistencies between videos, exercises, and slides.

By Vasudevan D

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Jan 28, 2018

Too much concepts to learn and practice. Course material can be little more engaging and split accordingly.

By Maxim M

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Dec 10, 2017

Very difficult lectures. You need a solid statistical background to keep up with the pace of the professor.

By Deleted A

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Mar 2, 2017

The ideas and concepts explained here are really important but are explained/written in a bit messy manner.

By xuwei. l

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Sep 22, 2016

lectures notes is not details enough, had to google around other materials to grasp the courser work better

By Muhammad M A S

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Jan 11, 2021

It's very important and very helpful, but it needs to be of more time/low speed to be perfectly absorbed.

By Rezoanoor/CS/Rezoanoor R

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Mar 13, 2020

It covers a lot of topics, good for that but submitting assignment via Swirl is extremely boring.

By manuel s g

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Jul 5, 2020

This is module where I have learn less. Instructor also was not dynamic as previous ones.