# 学生对 约翰霍普金斯大学 提供的 统计推断 的评价和反馈

4.2
4,279 个评分
863 条评论

## 课程概述

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....

## 热门审阅

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 .

MI
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!

## 101 - 统计推断 的 125 个评论（共 831 个）

Jul 9, 2021

Statistics was not, to put it mildly, my favorite subject in college. This class, however, managed to actually get me involved in the subject as it is tought with applicability in mind. Thank you.

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.

Oct 4, 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!

Apr 7, 2020

Very good course for the beginners who want to learn about statistical inference, R programming. A good explanation with the helpful R exercises makes us understand the concepts very easily.

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!

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.

Dec 9, 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.

Dec 13, 2020

it was a very challenging course, but entertaining too. The course has a very good complement with additional material that helps to better understand the contents of each of the subjects

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!

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.

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.

May 9, 2020

Course is compressed and good to learn in short span. The illustrations and projects are really helpful to learn the concepts and implement. I really enjoyed through the course

Jun 6, 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 ;)

Dec 4, 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.

Oct 28, 2020

I think that this course is great. I particular like the practical exercises ; which gives hand on experience with the bit complex theory. I could miss more training quizzes.

Jun 3, 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.

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.

Aug 14, 2016

Outstanding material. You can scale the difficulty and depth on the subject as you wish. Great source and references. (Recommend seeing the videos at 1.5 x speed though).

Dec 7, 2018

The course was quite technical and difficult, but the lectures of the teacher helps to understand the main points and reading the ebook of the course helps a lot as well.

Oct 24, 2016

Great course ! Important for those who are either going to take the Regression analysis or those who are working with data and want to do same basic hypothesis testing.

Jun 2, 2020

It's good as a reminder course, but I recommend coming with some prior knowledge.

My recommendation to the instructors, update the course material, at least the videos.

Jan 3, 2021

Thank you Johns Hopkins University, thank you Coursera. I congratulate you on fulfilling your mission to provide universal access to the best education in the world.

Nov 2, 2018

More practical exercises with R (like a pre-exam of examples with exercices) would give more opportunities to practice and understand the matter (R implementation).

Oct 11, 2020

Many thanks for this course! I learned a lot of things that i've never imagined that i would manage to learn! thanks for everyone who makes this become possible!

Mar 9, 2018

This course was very helpful to remember so concepts of statistical inference. The swirl and project exercises helped me to practice more my R-programming skills