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....

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!

필터링 기준:

교육 기관: Eduard R

•May 26, 2020

Connection between the slides, transcript, R code, and pdf presentation slides and the text book is great! Easy to follow along. Concepts are explained poorly. Often definitions are missing and the student has to guess what is meant by a variable on the slides. Very superficial learning. Not nearly compareable to real university course. I think the students would benefit from more project work assignments and peer reviews. This is when you really learn something - when you have to do it yourself. Quizes are a good start. I did the course as a refresh and I can't imagine correctly understanding the concepts just by having completed this course.

교육 기관: Ricardo M

•Dec 29, 2017

The course delves into some relevant topics however it doesn't feel as properly structured. While on the first week the lectures seem to try to give a basic and comprehensible learning of probabilities, once we start into the topics of pure statistics, it's just gets a mess.

Lots of formulas and concepts thrown at you without much clarification. For someone without any knowledge/background on statistics this can be quite difficult to grasp the concepts.

The course should be reviewed or at least the indication of "eginner Specialization.No prior experience required." should be updated to mention that some knowledge in statistics is recommended .

교육 기관: Thomas G

•Apr 05, 2017

This course seems weirdly balanced between assuming one knows very little about statistics while also assuming one is intimately familiar with statistics notation and terminology. It would probably be better if the data science track had an optional "intro to statistics" class that can take more time to let students familiarize themselves with the terminology, and then a separate "ins and outs of probability testing in R" for those already familiar. This course seems to try and bite off more than it can chew by attempting to be both at the same time.

Still, the lectures are interesting and the material is important to learn / cover.

교육 기관: Joana P

•Feb 22, 2018

I found that the materials given or the lectures never allow you to clearly follow a structure.

I understand that are so many contents to present, but jumping around from one to another is not the way.

Quite frequently a lot of the slides are just useless. Not all of us have the time to go behind every mathematics, so I would like to see more real examples of how to use the contents you teach us, than knowing all the mathematics and have a lot of slides to show how to deduct mathematically the probability of something to happen. But might be my opinion because I had other expectations.

교육 기관: Qasim Z

•Oct 26, 2016

This course means well but the lectures in the first half of the course are not good. The instructor seems to take a midway between rigorous mathematics, using terms like robust etc while at the same time also trying to keep it easily accessible. RD Peng's courses take a much better approach in that they keep things at one end of the spectrum (simple language). Having a background in theoretical physics and computer science, this duality in this course is very confusing for me. Also, I do not need to see a tiny, grainy video inset of the instructor during the lecture videos.

교육 기관: Christoph G

•Sep 13, 2016

I have to admit, that most of the videos confused more than they helped. For most of the topics I simply went to KhanAcademy and got it easily there and I was asking myself, why a topic was made so complicated. I have the same issue with the next course. I highly recommend to start visual explanations of what you want to achieve instead of throwing formulars at people and confuse them. IN KhanAcademy e.g. they do exactly this and you got the point and if you got the point, the formular wasn't such a big thing anymore.

교육 기관: Anant C

•May 06, 2020

The content of the course was well organized and structured, but the content delivery in the videos was terrible. I was unable to understand even the basic concepts from the professor due to his fragmented sentence structure, lack of lecture planning and an emphasis on evaluating R code more than on explaining the concept. I am now hesitant to go on to the next course in this specialization. The Swirl() exercises, however, were very thorough and did a good job in explaining the concepts.

교육 기관: Krishna U

•Jul 29, 2019

Terribly confusing, and concepts were made so much more complicated than needed (lectures, instructions, quizzes).

Most other sources (Khan Academy, Stattrek, Stats textbooks etc) were used and preferred to complete course, to completion of the Data Sciences specialization. Or just have a full understanding in Statistics prior to this course.

Additionally, there's little discussion or help; wish this course could've been updated with revisions or clarified over the years.

교육 기관: graham s

•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.

교육 기관: Christine L

•Nov 05, 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.

교육 기관: Charles K

•Sep 19, 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.

교육 기관: Thej K R

•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

교육 기관: Rajit A

•Apr 02, 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.

교육 기관: Jake T T

•Apr 08, 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.

교육 기관: Eugene K

•Mar 08, 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.

교육 기관: Omer A

•May 16, 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.

교육 기관: Stephane B

•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.

교육 기관: Patrick S

•Feb 09, 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.

교육 기관: Craig G

•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

교육 기관: Alex B

•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.

교육 기관: Mourad Y

•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

교육 기관: Arjun S

•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 :(

교육 기관: Rui P

•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.

교육 기관: Chandrakanth K

•Nov 05, 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.

교육 기관: Tanguy L

•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.