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Probability and Statistics: To p or not to p?(으)로 돌아가기

런던 대학교의 Probability and Statistics: To p or not to p? 학습자 리뷰 및 피드백

4.6
별점
928개의 평가
312개의 리뷰

강좌 소개

We live in an uncertain and complex world, yet we continually have to make decisions in the present with uncertain future outcomes. Indeed, we should be on the look-out for "black swans" - low-probability high-impact events. To study, or not to study? To invest, or not to invest? To marry, or not to marry? While uncertainty makes decision-making difficult, it does at least make life exciting! If the entire future was known in advance, there would never be an element of surprise. Whether a good future or a bad future, it would be a known future. In this course we consider many useful tools to deal with uncertainty and help us to make informed (and hence better) decisions - essential skills for a lifetime of good decision-making. Key topics include quantifying uncertainty with probability, descriptive statistics, point and interval estimation of means and proportions, the basics of hypothesis testing, and a selection of multivariate applications of key terms and concepts seen throughout the course....

최상위 리뷰

TS

May 01, 2020

I would like to thank Dr. James Abdey for his wonderful explanation of probability and statistics in a short time. I definitely learnt many things which I can make use in my further courses. Thank you

SR

Jun 24, 2020

Excellent introductory course for probability and Statistics, Dr. Abdey made the course very lively with his approach of teaching. Hope to see many more online courses from you in the future.

필터링 기준:

Probability and Statistics: To p or not to p?의 310개 리뷰 중 276~300

교육 기관: Rikitha

May 14, 2020

It was very nice to learn from the professor. He taught everything clearly

교육 기관: Naveed U K

Jul 09, 2020

The Course is good for those who already take it in school. :)

교육 기관: Dũng T N

Jun 22, 2020

Content is good but Lack of pictures, examples, quiz, homework

교육 기관: Ken J

Jun 15, 2020

A good introduction to fundamental concepts in prob and stats.

교육 기관: yammaji k

Jun 05, 2020

Testing of weather all bottles have 1000 ml interstimg

교육 기관: Lam S Y

May 29, 2020

Improving my knowledge in Statistics and Probability.

교육 기관: Alishir B

Apr 30, 2020

Course is good. But not enough for statistic science.

교육 기관: Arturo M

Jul 03, 2020

Great introduction to probability and statistics!

교육 기관: Jessie P

May 29, 2020

Helped me refresh my knowledge in statistics

교육 기관: Shubham U

May 16, 2020

It should have been more numerical based.

교육 기관: KV N R

Apr 24, 2020

Informative and useful to start analytics

교육 기관: Eyob

Nov 06, 2018

funny charming and full of numbers

교육 기관: Ritesh R

Jun 09, 2019

God course for beginners level.

교육 기관: Chaitanya K

May 19, 2020

very informative and helpfull.

교육 기관: Ichcha R

Apr 29, 2020

The host is really good....

교육 기관: Tanguy P

Apr 14, 2020

Very good beginner class

교육 기관: Suramya S D

May 14, 2020

well presented course.

교육 기관: Anamika S

May 06, 2020

I enjoyed this course.

교육 기관: Mayur P K

Sep 10, 2018

Great Course.

교육 기관: Kaushal S

May 24, 2020

Great course

교육 기관: Ahmad H J M J A

Jun 19, 2020

Thanks!

교육 기관: Aun A

May 22, 2020

In an introductory statistics course, there was no need of discussing the Monty Hall Problem, Decision Tree Analysis, Monte Carlo Simulation etc. Time saved by foregoing these could have been utilised for incorporating some mathematical rigour. Without math anyone's undertanding of statistics and its usability will always be restricted.

The PDF notes were a good thig to use in a MOOC.

교육 기관: VIJAY N

Mar 28, 2020

The subject was interesting and he did brought new topics which i liked but it was a bit draggy at times which made me to loose attention. Overall i liked it - especially the Monty Hall problem formulation and Bayesian update. The topic on p-value is still muddy for me.

교육 기관: yogita k

Jun 06, 2020

last week's content was too short. It will be great if one more week is added to the course where the students can learn more about decision trees, linear modeling, and regression.