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
4,218 个评分
853 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!

701 - 统计推断 的 725 个评论（共 820 个）

May 21, 2016

completely missed the explanation part of the teaching. Why use n-1 for standard deviation? "Because of degrees of freedom" Only mention, no further explanation. Just no explanations of anything in this course. I looked at the biostats course by the same guy. Same story. Teaching is more than just saying the facts, you have to explain things, lead the understanding. The materials are just not there, not in the book either.

Nov 5, 2016

If I wasn't already familiar with statistics, I would find the lectures and course book difficult to follow. If future revisions to the course are made, consider including a cheat sheet with the notation, parameter abbreviations used, etc. It would also be helpful to rewrite (or at least include a reference back to) the equation being used in the example calculations instead of immediately filling numbers in.

Sep 18, 2016

The instructors approach in this course is very cursory. He tries to split the difference in going through the mechanics/mathematical theory and practical applications. As a result, he fails at both. I think it would be better to leave the mathematics and application learning to supporting materials and focus on explaining the theory and concepts of statistical inference in the lectures.

Apr 14, 2019

The hardest course I have ever taken! Very hard to follow! Spent a lot of time, trying to understnad the lectures! The final assignment was really good, it really tied everything together! But the lectures and following them was a nightmare and hard to understand! I spent 55 hrs on this particular course! and the last week 4 I spent 20 hrs on this course

Apr 2, 2019

The course is very technical and needs a) reading and practice outside of the material presented here and, b) needs you to invest a lot more time than you might believe before you start this course. So if you are looking to just understand the basics of statistical inference or if you don't have a background in statistics then this is best avoided.

Apr 8, 2018

This was a difficult course to get through. The lectures were almost completely useless - I had to look up videos from youtube and other sources for every single lecture to learn the concept, and then rewatch the lecture - even then the instructor was difficult to follow. If this wasn't part of the specialization I would have dropped the course.

Mar 8, 2018

Good material but the lectures are not well put together for the novice. I think the professor needs to have a little more empathy for the students and not just read notes for the class. Too many sentences with esoteric terms are spewed out without truly trying to explain the material in a way that the student will understand.

May 15, 2016

this is heavy material, and I suggest it be broken down to two separate courses, and the author take his time in explaining the various concepts in much more detail vs. trying to cram them within 5 or 10 minute sessions. I know I wasn't the only one struggling to keep up with the teacher after week 2.

Apr 11, 2018

The content of this course is interesting and i learned a lot BUT it's indeed badly explained, and i lost a lot of time to understand certain things. My advice: watch others videos (from Khan Academy for instance) in order to understand the basics concepts and then, come back to this course.

Feb 9, 2017

Sorry to say, but for me as a non-native english speaker, most videos are hard to follow. Its because speaker talks fast, unclean and with bad sound quality. Of course I'm not used to the mathematical english terms. Also the many animations with the slides made it hard for me.

Jul 26, 2017

It may be that this is the first Math heavy course in the data science specialisation, but I found this one really hard going, with the videos being particularly hard to follow. I had to do a lot of extra research to find alternative explanations of the concepts involved

Dec 29, 2018

Doesn't really teach you stats, gives you a rough idea but only shows you that it's possible in R. Doesn't really explain what it's doing or how to do it, rather "here's a handy R function that does this". Meaning I'm just learning R rather than any actual stats.

Nov 26, 2017

True the content is rich, but the instructor is not engaging and much content is not well explained so the learner should search everywhere. If it is to compare with khan academy videos for example, they are much more coherent and way too easier to understand

Sep 17, 2017

To someone new to statistics, this course does NOT help. The professor does not seem too interested or enthusiastic and seems like he is reading off the slides. Concepts are not explained clearly at all. Forced myself through this course :(

Oct 10, 2016

Despite the pertinent content, the way the instructor gave the classes could have been way more intuitive. You'll find videos on the web that can help you with the subjects covered and do a better job explaining the concepts. Disappointing.

Nov 5, 2017

Some concepts are advanced and it requires detailed knowledge of statistics. It would be good to add a chapter to explain the basics before going through advanced concepts. The explanation in some of chapters are very basic.

Feb 25, 2017

This course should not be presented by video. I loose lot of time by learn with others supports than Coursera.

Even if I notice and appreciate the works to produce these supports by the teacher, I'm not a big fan at all.

Dec 29, 2018

this is a difficult subject that takes a lot of practice to understand. would like to see the course time and materials extended. It would also be helpful to have live online sessions with instructor and classmates.

Mar 21, 2018

I think the course was very informative but it took me about 3 months to finish course. Lot of important concepts have been condensed to one or two slides which makes it really hard to grasp the concept quickly.

Nov 27, 2016

This course is great, but Brian is certainly not a good instructor. He does not explain things well, and articulate examples. I had to take Statistical Inference from Duke university to pass this course.

Oct 14, 2016

This course is poorly taught. The instructors often speed through significant concepts and are generally unable to explain the concepts clearly to someone who does not have a major statistics background.

Mar 3, 2016

Taught very quickly and assumes a high degree of math fluency. Only take this if you are either very fluent in math already or have a significant amount of time to devote to understanding the material.

Jun 13, 2016

Very poor instruction and organization of topics, very poor explanation of core concepts. I learned more from reading other sources while taking the class than I did from the lectures.

Jul 10, 2019

The topics are very interesting and there is no dude that the teacher knows wath he is teaching, even though I think it can be better with more grapics splanations and less formulas.

Jul 5, 2017

A lot of the course were not explained in a way that made it easy to understand for a neophyte. I had to go re-watch most of the lessons on khan academy to understand the principles.