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Avis et commentaires pour d'étudiants pour Inférence statistique par Université Johns-Hopkins

4.2
stars
3,588 évaluations
691 avis

À propos du cours

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....

Meilleurs avis

JA

Oct 26, 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 .

AP

Mar 22, 2017

The strategy for model selection in multivariate environment should have been explained with an example. This will make the model selection process, interaction and its interpretation more clear.

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51 - 75 sur 658 Avis pour Inférence statistique

par Rongbin Y

Sep 17, 2019

The course provided a great overview of the base statistical knowledge required for advanced data analytics. I had gained great experience and exposure to sophisticated hypothesis making and data wrangling skills. Thank you.

par Tine M

Mar 02, 2018

The course was at times difficult, I found that extra research was needed to fully understand what was going on. The extra questions related to the homework questions are a great way to test your understanding of the class.

par Matthew C

Nov 03, 2017

One of the better courses so far in the Data Science Specialization. If you have no background in statistics, expect to spend a lot of extra time in this course, especially weeks 3 and 4. Tough, but lots of good material.

par Matthew S

Feb 10, 2019

Excellent course if you have some background in math or stats already. This course might be difficult if you don't have that background. The peer graded assignment does a good job tying everything together in my opinion.

par Bill S

Oct 02, 2017

This was challenging and informative. I think the time estimates are way off though. Some things estimated at 2 hours really took 10, and things that are estimated to take hours are one paragraph to read and then over.

par Vinodkumar V

Oct 10, 2017

Rigorous but worth... though it skims the SI topic, at least introduces to the vast dimensions of the subject. It takes time, but one learns. Follow the exercises in the book in addition to swirling. It helps a lot.

par Marc T

Apr 01, 2019

Not only did this course help me to understand concepts that I have encountered in my job over the length of my career, but it also introduced me to using R Markdown, which will come in handy for future projects.

par Angela K

Dec 03, 2018

really great course! takes a few minutes to get used to Brian after having all courses taught by Roger. I finally understand hypothesis testing and confidence intervals after taking several classes on this topic.

par Shashikesh M

Jul 17, 2017

This is one of the most important course in data science specialization series, everyone should take this course very attentive way, because it give very deep insight about the role of statistics in data science.

par Jacob A

Oct 26, 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 .

par Keidzh S

May 16, 2018

Everything absolutely amazing. Sometimes there were some troubles with audio files, but I think it doesn't affect on the course. Because I have no trouble with understanding. Thank you to al masters!

par Luiz E B J

Nov 11, 2019

É um curso excelente que me fez rever muito conceitos esquecidos ou que simplesmente passaram batido durante a minha formação. É um abordagem prática que traz o que é mais relevante no assunto.

par Long H

Jan 31, 2016

I found this course really good introduction to statistical inference. I did find it quite challenging but I can go away from this course having a greater understanding of Statistical Inference

par Svetlana A

Oct 04, 2016

Well balanced course with a lot of practical examples which help to understand the theory. I apply statistical inference methods myself, and nevertheless I've found new topics here. Thank you!

par Johannes C F

Oct 23, 2016

Brian is a very good lecturer. Even though he is knowledgeable, he goes through everything step by step and makes sure you don't fall off the wagon at any point. I had fun doing this course!

par Matti N

Dec 10, 2017

After many years had passed since my last encounter with statistics this course proved to be quite some work to complete. Nevertheless, still a great course and definitely worth your while.

par Aki T

Dec 09, 2019

In my opinion, this course is fundamental to Statistics and therefore Machine Learning. It is well explained, although it requires students to work on more mathematical aspect in parallel.

par 李俊宏

Aug 24, 2017

Professor Brian has very explicitly introduced the basic ideas of statistics! I have learned a lot of fundamental ideas which make me more confident in doing statistics. I really like it!

par Pankaj K

Oct 16, 2018

This course covers the very basics of statistical inference which will help to strengthen your base concept. I loved doing the course especially the practice assignments on swirl.

Thanks.

par Samer A

May 22, 2018

Very good and informative. I'd had statistics back at the university but I never understood the underlying principle of hypothesis testing. Mr. Caffo makes it look pretty clear and easy.

par David B

May 23, 2017

Excellent course. After completion, I really feel like I have a great grasp of basic inferential statistics and this course introduced ideas that I had not even considered before.

par Mark F

Jun 06, 2018

Loved the course, also very pleased that there was recommended reading for further study. Also loved Brian Caffo's deadpan joke delivery, really hard to know if that's an act ;)

par Yatin M

Dec 04, 2017

If you work through all the examples, you will be pleasantly surprised. This is an awesome course. Highly recommended. Many thanks to Brian Caffo for improving my understanding.

par Pranay R

Jun 03, 2019

A very conceptual course to understand the fundamentals of Inferential Statistics. I would recommend this course to all aspiring data analysts/scientists or business analysts.

par João F

May 14, 2018

Very intensive and demanding course with interesting examples. Students without previous knowledge in statistics will likely need additional resources to complete the course.