Chevron Left
공중 보건학의 가설 테스트 (으)로 돌아가기

존스홉킨스대학교의 공중 보건학의 가설 테스트 학습자 리뷰 및 피드백

4.8
별점
529개의 평가
129개의 리뷰

강좌 소개

Biostatistics is an essential skill for every public health researcher because it provides a set of precise methods for extracting meaningful conclusions from data. In this second course of the Biostatistics in Public Health Specialization, you'll learn to evaluate sample variability and apply statistical hypothesis testing methods. Along the way, you'll perform calculations and interpret real-world data from the published scientific literature. Topics include sample statistics, the central limit theorem, confidence intervals, hypothesis testing, and p values....

최상위 리뷰

MM

2022년 5월 5일

This course astonishingly improved my ability in interpreting scientific paper results related to public health. Highly recommended. Thanks in advance to Dr. McGready for being such a great instructor

SF

2020년 5월 21일

You have to use outside sources and practice questions to really understand the material. This course makes you think and demands that you know the information. It was a great class. Thank you.

필터링 기준:

공중 보건학의 가설 테스트 의 130개 리뷰 중 51~75

교육 기관: Adnan A

2020년 4월 23일

I love the way how the Instructor builds on previous course. very simple and conceptual explanation of the concepts.

교육 기관: Muhammad A

2020년 7월 18일

It's a great course regarding hypothesis testing. You will see a lot of examples that will make you get the topic.

교육 기관: Muhammad F b M R

2020년 5월 30일

Very good teaching by the instructor. Great course to get intuitions behind the statistical analysis. Thank you.

교육 기관: Divya G

2019년 4월 13일

It was a great course i thank our guide he teaches so well. thank you so much for wonderful learning experience.

교육 기관: Christos K

2020년 4월 6일

Fantastic course! It hepls you understand key concepts of biostatistics, which are essential in medicine today.

교육 기관: Sampoorna R

2020년 10월 29일

Well-structured and seamless continuation from course 1 syllabus. Detailed explanations. Highly recommended!

교육 기관: Ezeobi O

2019년 4월 8일

I use to hype p-value a lot but this course made me appreciate the place of p-values in a study.

교육 기관: Paul H

2020년 2월 25일

Very carefully and well explained material with numerous examples that clarify the material

교육 기관: Jesus M V H

2020년 10월 3일

I learned a lot, lots of examples for you to understand. I highly recommend this course :)

교육 기관: Vicente P M

2020년 7월 22일

This course has helped me so much to fully understand the results presented in studies.

교육 기관: Dr S T

2020년 4월 21일

This is a wonderful course. John has presented complex ideas in a simple and lucid way.

교육 기관: Ricardo F

2020년 3월 8일

Excelent course!! well explained, and a lot of practice to learn in a easy way model

교육 기관: SOMSE I

2019년 4월 24일

It was an amazing journey for me in this course. Thank you for making this possible!

교육 기관: Lauric E

2020년 11월 23일

Very informative and appreciate all the examples given to understand the concepts.

교육 기관: Enyerbert G

2021년 2월 11일

As future public health inspector this course is perfect for improving my skills

교육 기관: Judith N

2021년 7월 7일

I really enjoyed the course. Thank you Coursera and John Hopkins University.

교육 기관: PRASHANT V

2020년 8월 17일

Awesome , such a lucid explanation of a complex concept. Really liked it !!

교육 기관: Maria V

2021년 11월 24일

really good course for beginners in biostatistics, very easy to understand

교육 기관: Sumaiya I

2021년 4월 4일

It was a worth taking cours. Learned the nuances of hypothesis testing.

교육 기관: Graeme S

2020년 1월 14일

Enjoyed the course and found it very useful and applicable for my work

교육 기관: Amri R

2020년 6월 8일

Great lecturer, comprehensive materials, and passionate-made course!

교육 기관: Nishat Z

2021년 10월 2일

An excellent course for understanding how hypothesis testing works

교육 기관: Steven B

2022년 4월 2일

excellent course - exceeded my expectations for virtual learning!

교육 기관: Abdullah f

2021년 12월 21일

As with the previous course, Wonderful explanation by Dr. John...

교육 기관: Cassandra N

2019년 7월 16일

Very well organized, thorough, and well explained. Thank you!