Multiple Regression Analysis in Public Health (으)로 돌아가기

4.7

별점

133개의 평가

•

31개의 리뷰

Biostatistics is the application of statistical reasoning to the life sciences, and it's the key to unlocking the data gathered by researchers and the evidence presented in the scientific public health literature. In this course, you'll extend simple regression to the prediction of a single outcome of interest on the basis of multiple variables. Along the way, you'll be introduced to a variety of methods, and you'll practice interpreting data and performing calculations on real data from published studies. Topics include multiple logistic regression, the Spline approach, confidence intervals, p-values, multiple Cox regression, adjustment, and effect modification....

Jul 26, 2020

lecture pattern gives enthusiasm in learning and solving quiz sessions. explanations for the solutions gives immense strength and confidence in learning. Excellant course and marvellous experience

Apr 24, 2020

This course covers all types of Multiple Regressions. Instructor explained the complex topics in simple language. Relevant examples from clinical field and thorough explanation by the Instructor.

필터링 기준:

교육 기관: Shady M S

•May 25, 2019

the course spends a lot of time repeating the same concepts. i would be more convinced if they spend more time in explaining how to make the multiple regressions , how many variables i can add and what are the limitations and how to make a measure of fitness

교육 기관: Anurag M

•Jan 21, 2019

Would love to learn more from Dr. McGready in statistical courses more advanced than the ones offered in this specialization

교육 기관: Michael K

•May 08, 2020

I thank Professor McGready. He's enthusiastic and he really tries to make sure that you learn the materials. I really appreciated the fact that he uses several case studies from course 1 to this course so we can see how the material we learn is applied to the familiar fact pattern. The repetitive examples also reinforce learning. I just have a suggestion. From my perspective, and, I've taken many MOOC courses, the lecture-quiz approach works, but it can be enhanced by hands-on exercises via R or even spreadsheets. But, that was a minor point. In sum, thank you for the great specialization. I learned a lot.

교육 기관: Konstantin G

•Jan 02, 2020

This is a phenomenal course to follow through and gain an understanding of the role data plays in healthcare. Sometimes something very small in nature has a huge effect, and it was awesome learning how to articulate and prove that during this course.

교육 기관: Justin C

•Nov 02, 2019

Very helpful in your explanations verbally and visually. It really helped me understand how to read and understand the cox regression model.

교육 기관: DHARMALINGAM G

•May 01, 2020

This course is good but kindly add minitab or other software to analyse the regression model equation,so that software based learning is very much useful for researcher. Assignment questions give some software tool to analyse the regression submission .

교육 기관: Billy C

•Jul 24, 2019

Duplicated video in the logistic regression module. I've raised a concern request correction of the issue but no response, and now I've completed the course already.

교육 기관: Bradley L A

•Apr 10, 2020

i dont like statics

교육 기관: Jennifer O

•Mar 31, 2020

Great conceptual introduction to multiple linear and logistic regression. As it covers some more advanced topics, many of them rely heavily on "letting the computer do it," but this course will emphasize the concepts you need to understand in an output.

교육 기관: Sukanya

•Jul 28, 2020

Excellent course. What I couldn't learn from years of racking my brains reading books on statistics, asking doubts and watching YouTube videos, I have been able to understand conceptually after watching this series. Very very helpful.

교육 기관: Dr K K

•Jul 26, 2020

lecture pattern gives enthusiasm in learning and solving quiz sessions. explanations for the solutions gives immense strength and confidence in learning. Excellant course and marvellous experience

교육 기관: Bhalchandra V

•Apr 24, 2020

This course covers all types of Multiple Regressions. Instructor explained the complex topics in simple language. Relevant examples from clinical field and thorough explanation by the Instructor.

교육 기관: Ulrick S K K

•Jul 30, 2019

The course is well structured. The numerous examples and practice questions help the student apply the concepts learned. I love the fact that almost every question was from a real article.

교육 기관: Anirudh

•Jun 21, 2020

Excellent Course. The video lectures are thorough and provide many examples to help explain the concepts. If this professor produces more courses, I will certainly take them.

교육 기관: Cassandra N

•Aug 31, 2019

The course was five stars, there were some quiz issues and a few numerical issues, but I learned a lot and appreciate the time and effort put into the content. Thank you!

교육 기관: Christos K

•Apr 09, 2020

Fantastic result. Mr McGrady is a fantastic teacher and explains difficult mathematical stuff in a simple and nice way. The course was very enjoyable!

교육 기관: Francisco G C N

•Aug 02, 2019

Incredible way of teaching biostatistics using by just adding more complexity to the same exercises in a gradual form!

교육 기관: Saumya R P

•Jul 02, 2020

one of the finest courses on biostatistics, in order to get refreshed with the core concepts and applications!

교육 기관: Abigail B

•Apr 22, 2020

A wonderful look at multiple regression, including effect modification, interactions, and adjusted slopes.

교육 기관: Dr G K

•Jul 26, 2020

Very much informative and educative videos and systematically designed quiz sessions. Real treatise

교육 기관: Md M

•Jun 21, 2020

thank you everyone for give me a chance to learn more thing from this coursera courses

교육 기관: Meghan S

•Apr 06, 2020

A wonderful course with a wonderful instructor. I learned a lot!

교육 기관: Fred L

•Jul 15, 2019

Great instructor, really informative and engaging.

교육 기관: Muhammad F b M R

•Jun 01, 2020

Learned a lot from this course! Thank you!

교육 기관: Tehreem H

•Jun 30, 2020

Amazing course! I learnt a lot.