This course is a little less clear than the first 2 courses of the specialization and there were a few technical problems (quizzes' answers and videos) and organisational issues. But the instructor remains very engaging and I enjoyed learning about the simple regression analysis.

The course, as well as the rest of the specialization are designed for statisticians rather than MDs and it's a pity that the amount of math in the course constantly take away its clinical scope. It's so much math-heavy that other very important principles of public health are scarcely mentioned, like the types of statistical tests depending on the variable types. Yes there are a lot of examples from the literature but there is absolutely no indication on how to use the formulas on a computer program, which program is best for what purpose etc., which could greatly enhance the usefulness of a course like this. Otherwise you need to attend other courses as you lack the practical skills of applying the statistics into action.

Also, the instructor should not just constantly read his bullet points from the slides, rather than try to explain the material in his own voice.

The Question and Answer section needs a few corrections, some incorrect answers are marked as correct. Simple linear regression analysis with continuous predictor is missing and the one for logistic regression in used its place.

I think, if the instructor showed how he computed the formulas, it would be great for the students. Most of the pictures are not clear.

Overall the course will give you an Idea. I thought lectures were long and too much explanation makes it harder to concentrate. Each lectures have 2 or 3 points, which could have been communicated in a simple manner. The instructor gives lengthy explanations and I felt lost.

Some the exercises had errors.

During lectures instructor starts writing with pen, instead, he could have written it before and explained in shorter sentences.

In exercise feed backs, our responses were not shown, which was makes it harder to know our answers and rectify our mistakes.

It also would have been helpful to recommend a software and to actually show us how to organize the date and how to use software.

Overall I felt that course was theoretical and I could have learned the concepts in 1 to 3 days, instead of going through lengthy lectures

I do need more clear definitions rather than examples.

There are few corrections/confusions in the computation of some examples given. Nonetheless, the topics are very interesting, and the instructor is very engaging. There are many examples and i like how Mr McGready organized the topics and explained every important point.

Great course! The organization and explanations were a little confusing for this course and the exams compared to the others. Despite this, I learned a lot of useful information and appreciate the effort and organization dedicated to helping students learn the material.

The course is an excellent introduction to simple regression, mixing theory, straight forward techniques for calculating and understanding outcomes, as well as numerous examples of a practical nature. Professor McGready does a very nice job of explaining the techniques involved. Having said that, it would be helpful to have a technical editor go over the slides and the various formative, summative and project quizzes, for not only this course, but the two previous courses. There are a number of small typos in the slides and quizzes, as well as a few instances of linguistic ambiguity that might give pause to a speaker of English as a second language. However, I want to be very clear, for me this was a very enjoyable experience.

The calculation has not been the problem. Otherwise, understand the questions and explanations that implies the difficulty and uncertainty to write the correct answers and solve the requested work. The course is well-structured for people who study alone, without asking the instructor or the mentors in the forums, but looking for support elsewhere. Grateful for all the material and some colleagues who have sometimes supported my questions. Sincerely!

Complex analyses clearly explained, with an emphasis on interpretation rather than on mechanics. Excellent examples from published literature used throughout. Highly recommended!

Thank you so much for a beautiful explanation and presentation of topics that a lot of physicians tend struggle with, by making it understandable and logical

Good course, but material is presented very quickly and tests don't necessarily do a good job at measuring what is actually taught. I would not suggest for someone with absolutely no background or experience taking a Biostats course. I'm taking as a refresher and the concepts are presented in a very fast paced way.

It would be nice to actually have the data and be able to do calculations with it rather than just talk about the calculations someone else did.

Another excellent course. John McGready really explains the subject well using examples from the scientific literature and lifting the lid to show how the results were obtained, how they should be interpreted and any pitfalls to avoid in interpreting them . I never thought I would really understand statistics although I could crunch out the numbers. Johns series of courses really give those numbers meaning and make it possible to really dig down and interpret what the statistical results in a scientific mean.

McGready is an excellent lecturer! Really takes the time to explain concepts in detail and provides heaps of examples, which help to translate concepts that would otherwise be quite abstract, into tools which are easy to understand and use in practice. I really enjoyed this course and all others in the specialization

I really enjoyed the course; I wish there were more practice questions and more detailed analysis on what and why I got questions wrong on practice quizzes/exams. That would have been very helpful in my ability to learn simple regression analysis.

Excellent course, excellent instructor. He's accomplished the explanation of complex statistical methods using simple, easy to understand language. The order of the lectures is coherent and leads the learner to achieve the objectives.

Very good lectures with multiple examples from literature. Conceptual course, amazing and must-watch one before learning how to do the computations, or if you want strong foundation for interpreting data analysis in literature.

Excellent course and specialization - software agnostic unlike most online courses, this gives a good understanding of the underlying concepts and calculations John McGready is an excellent teacher - thank you John