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

4.2
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4,054 évaluations
806 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 .

MI

Sep 25, 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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51 - 75 sur 773 Avis pour Inférence statistique

par Jose A R N

Mar 31, 2017

My name is Jose Antonio. I am looking for a new Data Scientist career ( https://www.linkedin.com/in/joseantonio11)

I did this course to get new knowledge about Data Science and better understand the technology and your practical applications.

The course was excellent and the classes well taught by the Teachers.

Congratulations to Coursera team and Teachers.

par chirag y

Jan 27, 2016

It was a good course especially for beginners like me. Though i would advice to continuously keep digging more about other packages also and also going through stack overflow for various hurdles encountered during doing programming assignment.

I would recommend this course to everyone who wants to know about data analysis using R language in particular.

par Olga H

Dec 29, 2017

Very illuminating and well taught. I think this is content every data scientist should master to begin with. I recommend following this class if you did not learn it in this way already at university, which might be the case if you are in exact sciences. And even if you did, this course might be useful to brush up your skills.

par Paul C

Feb 11, 2017

Kudos to Caffo for using charts and examples to provide a lot of insight without using a lot of math. However, I would personally like the math to be presented, too (e.g., the 'off-center' T-distribution, etc.). This could be done is special sections of the book and lectures, as is done in the Regression Models class.

par Qian N

Apr 16, 2017

The course materials are well designed and delivered. I have taken basic inferential statistics at various levels in the past like 5 years, this is a really nice refresh and update (with respective the use of R). I would recommend this courses taught by Dr. Brian Caffo to others who are interested in the subject.

par Max M

Feb 21, 2020

Tought. Took me around 3 months to complete. I also took extra courses and bought a book to help me out on this one. Is not easy if your background in statistics is not already solid. But once you finish and you find yourself running simple statistics in R then everything is very rewarding!. Very good course!

par saul c

Dec 12, 2016

Although the instructor is very good, it would be nice to have a direct link to more references that explains the basics without skipping certain steps that a beginner may find difficult. The course is pretty good and if the student is proactive he/she will find a way to self-learn those missing steps :)

par Gopinath V

Aug 27, 2017

I didn't find time to sit for this course as I was involved in other activities. So also whenever I get time to see the lectures, I felt I need to see the previous slides/lectures. And I did go back then and after. But the course content was good. The instructor has the command over the subject.

par Joseph M

Dec 04, 2015

This is an excellent course for anyone who needs a better understanding of statistics and that includes all professions that deal with quantitative data. It helps you become a better citizen by helping you decide when something is mere chance and when mere chance would not explain the events.

par Lucia F M

Jul 17, 2017

Awesome course if you need to understand the theory behind the statistical test you keep reading in scientific articles, if you wanna get the basis with which to learn more complicated regressions models, or if you have studied statistics before and forgotten most if it !

par Sanil S

Jan 14, 2019

The course starts from very basic probability piece which is great for beginners and covers all relevant topics. I found that some of the topics difficult to grasp. However I did supplement this course by seeing Youtube videos from jbstatistics and Marins stat lectures.

par 李佳童

Dec 01, 2015

Dividing a week's contents into modules and adding a brief introduction at the beginning of each module makes the course much more clear. Students can also know what programming assignments (swirl) they should do every week. I appreciate those changes in the new class.

par Charles M

May 27, 2019

Elegant presentation materials and contains evaluation materials that target essential concepts and learner's ability to apply course information. Very well done and looking to take the biostatistics bootcampe alluded to in the lectures, by the same professor (Caffo).

par BALSHER S

Feb 03, 2017

This is a good course to set up for further learning. One gets exposure to topics in intro and intermediate statistic and starts to grasp how intricate the web of statistics it all the while the focus is on Hypothesis testing which is one cornerstones of statistics.

par Craig L

Dec 05, 2016

This is the toughest content yet of the Data Science specialisation but probably the most valuable piece so far. Video content is good but moves along very quickly so finding another book on statistics to back up the course content will be a great benefit.

par Greg A

Feb 22, 2018

Very good course, but definitely a challenge. There is no shame in watching some of these lectures multiple times. I would recommend taking all of these quizzes until you can get 100%. It will help you out a lot in the regression and machine learning

par Nino P

May 24, 2019

It's basically introduction to statistics. I have taken them as part of my education so it was a bit easier for me, but I think somebody new to this can lear a lot. It's a bit harder than first 5 courses, but still important and well teached.

par Edén S

Jul 27, 2020

At the beginning I've found a bit hard to store so much information on Statistics, but it is worth making the efforts, since the shown tools equipped a data scientist with strong arguments so as to refuse or accept some conclusions on data.

par 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.

par 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!!

par 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 ..

par 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.

par Julio C R N

May 17, 2020

Loved it. Some courses have an automated voice. But I was lucky enough to get an iteration with a human. I always wondered the reasoning behind some statistical analysis and this shows you the basics to understand those concepts.

par 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.

par Pablo D C

May 09, 2020

Such a good course! it is a very dense one, but Brian is a really great teacher and knows who to explain wonderfully. Furthermore, there are many examples and online activities which help you to understand better the concepts!