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Opiniones y comentarios de aprendices correspondientes a Inferencia estadística por parte de Universidad Johns Hopkins

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3,652 calificaciones
715 revisiones

Acerca del Curso

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....

Principales revisiones

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 de 683 revisiones para Inferencia estadística

por Roberto D

Dec 13, 2016

I learned a great deal from this course. Methods, testing and most of all logical processes with proven with evidence. I understand this course only touches the surface, but it will serve me as a catalyst to continue exploring the field.

por Rosa C V

Feb 03, 2020

Muy contenta con el curso. Tenia un poco de temor de que se me haga muy complicado, pero las clases estuvieron bien diseñadas y pude concluir este y otros 4 cursos de la especialización en Data Science con exito :-). Muchas gracias!!

por Damjan S

Jul 09, 2017

This one is one of the more mathematical course in this specialization, few times to the library and help with friends who are in the field of statistics or biomathematics would be very beneficial.

Dont skip any swirl practices ..

por Regis O

Aug 29, 2016

This course covers a wide range of powerful statistical concepts. The best way to work through this is to run R code as you go through the examples. If you are not comfortable with R, make sure to take the intro to R course first.

por Tarek L

Dec 13, 2018

Dr Brian DeCaffo is a talented and forward thinking educator. The amount of supplementary material he brings to the course is a bountiful bonus that really helped me grasp concepts. One of the best courses I've taken on Coursera.

por 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.

por 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.

por 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.

por 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.

por 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.

por 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.

por 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.

por 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.

por 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.

por 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 .

por 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!

por 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.

por 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!

por 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!

por 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.

por 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.

por 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!

por 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.

por 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.

por 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 ;)