Brian Caffo, PhD
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. The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life–long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
Instructor Details
Courses : 7
Specification: Statistical Inference
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60 reviews for Statistical Inference
Add a review
| Price | Free |
|---|---|
| Provider | |
| Duration | 16 hours |
| Year | 2015 |
| Language | English ... |
| Certificate | Yes |
| Quizzes | Yes |
Yiyang Z –
A lot of materials covered
Koen V –
Hard subject, hard explanations
BOUZENNOUNE Z E –
A great course. Needs a great follow up from the student.
Bla~ Z –
I know this is a very shallow dive into the field, yet I have the feeling I could have learned more. The absence of judgment whether my calculations in the project were correct or not was confusing too me since in statistics it’s more important to correctly interprete the result then to get the result. Calculation and interpretation of results should become routine and more different, practical, coding exercises would be very cool to have. Having that said, I still much appreciate the Data Science Specialization as a whole.
Connor B –
The course project was the most beneficial for me because I got to work with real data it helped me understand the concepts much better.
FAIZAN D –
useful
Robert H –
Very good course, well detailed and a nice introduction to Statistical Inference.
Robert J C –
Good introduction to statistical inference.
Kripa G –
Finding time to sit and do the assignments and peer review was a challenging this..but still I got through!
carlos j m –
Great content
Muhammad Z H –
learning alot
Rongbin Y –
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.
Carolina G –
Muy organizado, con temarios interesantes y mucha claridad en los contenidos
Moshe P –
Very difficult course even for someone who had learnt Mathematics and Statistic at the University level. Many concepts were very tersely explained with very few examples. The course book definitely helped. I would say two semesters of Statistics were squeezed into this course. Homework work exercises were very interesting and interactive.
John M –
This course was very hard to complete. The lectures were harder to follow than the previous courses.
Audun T H B –
Thorough course. A bit difficult to follow the lectures at times.
Rizwan M –
good
Nithiwat S –
Very horrible course. This course is a good example of how to design a bad online course and teach a complex material so it’s more difficult to understand. I’d give other courses a shot instead of this one, unless you want the specialization. First, the course should have listed R programming as a prerequisite. Second, instead of only reading the definition of terms, he should have explained what they are and give example. I spent more than 4x of the video lecture length, trying to think and follow, but I still didn’t understand. No example, no explanation, just *reading* the definition right off the text book using mathematical term. Math is complex, but it can be explained so everyone can understand. Third, I simply have a hard time understanding why the professor has to talk so fast and edit his video and/or make slides so text pops up in order to speed up the lecture instead of writing along as he speaks and explains (but there was no explanation in the lecture anyway so pausing the video to slow down wouldn’t help). It’s difficult to catch up or take notes when he edits video so text pop up very quickly. I don’t think there’s a restriction on the video. Overall, horrible experience.
Ashwin V –
Great course
Boris K –
This is so far the most difficult course in the specialization, but also the most useful. In this course you are taught to think like a scientist, to test hypothesis and provide evidence for your analysis. The lectures are succint and clear, the quizzes are clever and useful and the final project will make you create a very beautiful report while doing scientific work, which is the reason I started studying data science in the first place!
gerson d o –
Wonderful!!
Darky C –
Not details enough to truly understand inference
Bolaji O –
Statistical Inference into granule! Every time spent learning this course is worthwhile. Instructor, AWESOME!!!
Manpreet S –
Really Good
Ethan S –
Thanks for strengthening my statistical R skills.
Luiz E B J –
E um curso excelente que me fez rever muito conceitos esquecidos ou que simplesmente passaram batido durante a minha formacao. E um abordagem pratica que traz o que e mais relevante no assunto.
Chouaieb N –
The course content is very interesting and sums up fundamental aspects of statistical inference. But the way the course is presented is average.
Elaine E –
I’m sure he is super nice and smart, but Caffo is an awful instructor. I kept waiting for him to actually get to the explanation of what he is talking about, but he never does. He explains the equation…with the equation. I really like statistics, but he was beginning to change my mind and somehow I was actually unlearning everything I had learned from other courses in the past. I would highly suggest taking this somewhere else, I like the one from Duke on Coursera, she actually explained things and I could understand!
Fabien N –
I find the lectures sometimes not clear enough to answer the quizzes questions. On the other hand, the course provides material in many ways, which is very nice.
Jose A d C F –
Great course!
Michael O D –
Excellent and stimulating course, swirl tutorials very effective.
Stavros S –
Weeks 3 and 4 should have been split into 2 extra weeks to explain the concepts deeper and also have more exercises
kameron b –
good material, hands on experience was excellent
Dion F –
I’m in the middle of the course and I’m thinking seriously to abandon it… The instructor is simply very bad (he might be very knowledgeable, but he cannot teach at least in an online manner). I rarely leave negative reviews, but this time I couldn’t resist&
Aki T –
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.
JiapengSun –
The materials offered from this course is far away enough from understand the content 🙁
Nelly C –
There is a lot of theory in the course but it is not always treated with the necessary rigorousness; this creates confusion and makes it difficult to understand the basic concepts.
Manuel M M –
The content of the course is really good and so the practices. But the teacher does not know how to explain things and easy subjects are transformed into a difficult ones. I had to study other books to really understand the subject
Johnnery A –
Excellent!
Angus M –
An excellent course that teaches the important theoretical abilities and limitations of statistics.
Pedro M –
Really great!
Anton K –
the material is good although lacking in details
Marcela Q –
Terrible professor!. Too much theory, too little coding. However, the book is great. I recommend do not watch the videos just go to the book!
Tomasz S –
Very fast course… Additional reading required.
uttam K –
good course
vidhi j –
It is pretty difficult and needs research and homework to be done from the learner’s side
Amanyiraho R –
Every data scientist should take this course
Waseem A W –
fantastic
Alexander D –
Wouldn’t recommend for those learning stats. Try Duke’s course instead. This one was poorly taught.
Rosa C V –
Muy contenta con el curso. Tenia un poco de temor de que se me haga muy complicado, pero las clases estuvieron bien disenadas y pude concluir este y otros 4 cursos de la especializacion en Data Science con exito : ). Muchas gracias!!
Dasarathan S –
It is one of the most important courses in Data Science. It covers most of the mathematical portion and it is hard as well for a non mathematical student. For a minimum, every sentence will have any of the four words like distribution, sample, probability, variance, mean, median, standard deviation, etcetera. We have to spend enough time and to be very careful in understanding each and every sentence. But this course was nicely categorized by Brian Caffo & others, This presentation was the simplest one on probability & statistics, I ever saw and it covers majority of the basic concepts. Thanks to Brian Caffo, Roger D. Peng & Jeff Leek.
ONG P S –
Very good course. A lot of examples helping me understanding the theories.
Rob S –
Very good theoretical basics for working with data
Twesigomwe D –
Really good introduction to Statistical Inference and R programming. A bit intense but really worth it!
Tomas A M –
Course lectures could be a bit simpler. without that many theoretical demonstrations & more pragmatics summaries of the concepts.
Henk B –
Although the topic was very interesting, the way of teaching was troublesome. Teacher spoke often in a way as if he talked to specialists. So it was often hard to understand, and for understanding I needed to consult other sources
Jack F –
Very thorough in covering not only theory, but application as well.
Henk B –
Although the topic was very interesting, the way of teaching was troublesome. Teacher spoke often in a way as if he talked to specialists. So it was often hard to understand, and for understanding I needed to consult other sources
Lau I L –
Well prepared, but a little borrowing
Rose G –
Hard but rewarding. I have a hard times with maths in general, but stats I can survive !