Chevron Left
Вернуться к Statistics with R Capstone

Отзывы учащихся о курсе Statistics with R Capstone от партнера Университет Дьюка

4.6
звезд
Оценки: 207
Рецензии: 51

О курсе

The capstone project will be an analysis using R that answers a specific scientific/business question provided by the course team. A large and complex dataset will be provided to learners and the analysis will require the application of a variety of methods and techniques introduced in the previous courses, including exploratory data analysis through data visualization and numerical summaries, statistical inference, and modeling as well as interpretations of these results in the context of the data and the research question. The analysis will implement both frequentist and Bayesian techniques and discuss in context of the data how these two approaches are similar and different, and what these differences mean for conclusions that can be drawn from the data. A sampling of the final projects will be featured on the Duke Statistical Science department website. Note: Only learners who have passed the four previous courses in the specialization are eligible to take the Capstone....

Лучшие рецензии

JN
23 мар. 2017 г.

I think this is a very advisable course as a whole, The capstone offers a good occasion to put into practice what has been learned during the four previous courses and also works as a sort of review.

AC
12 июля 2017 г.

Great course, learned a lot and got me started on another project that I've turned into a really nice portfolio item. I feel much more comfortable with R and statistics principles.

Фильтр по:

26–50 из 50 отзывов о курсе Statistics with R Capstone

автор: Andrea P

8 окт. 2019 г.

Very interesting project oriented and practical case! Well done!!

автор: Andy D

3 апр. 2017 г.

The Capstone project really helped tie the program together

автор: Lou B V

10 окт. 2020 г.

It is great. You really have to apply what you learned.

автор: Marco G

13 янв. 2021 г.

Great project, real life application.

автор: Arjun B

22 февр. 2018 г.

Strong Capstone Project

автор: Gabriel T F

17 авг. 2020 г.

A very good course

автор: Marina Z

1 авг. 2017 г.

Great! Enjoyed it!

автор: Jim F

6 апр. 2018 г.

Loved this course

автор: Roland

2 февр. 2018 г.

Excellent course

автор: José M C

22 мар. 2017 г.

Great activity!!

автор: Oscar C R

5 дек. 2020 г.

Good Course

автор: Vinh H

12 окт. 2017 г.

Very good !

автор: Albert C G

1 июля 2017 г.

Great

автор: PAUL M

10 июля 2018 г.

V

автор: Bruce H

6 дек. 2017 г.

This project will reward you for the time you invest. It's a good simulation of a real-world exercise in using concepts from the specialization. The reason I took away one star is because the grading rubrics at every step are relatively superficial, sometimes absurdly superficial.

автор: Mariia D

22 мар. 2021 г.

Course is good, well planned and teaches a lot

However, there is a problem with the certificate info, it is said, that there where "5 weeks of study, 5-7 hours/week average per course"

It is misleading, as there were at least 25 weeks of study, 5 weeks per course at average

автор: Benjamin E

12 июля 2020 г.

Good, challenging problem sets. Final project is interesting enough, albeit perhaps could have required a bit more in the final submission to make it really rigorous.

автор: Matthew C

3 сент. 2020 г.

The capstone is difficult, especially the quizzes, but it's a great way to solidify the things you learned in the course.

автор: ninad p

7 дек. 2019 г.

This was my first course, and found it very useful to learn new skills.

автор: Tom M

15 авг. 2017 г.

Excellent

автор: Katy S

1 февр. 2021 г.

I liked the format of the course with its combination of quizzes & mini-peer review assignments which progressed towards the final project. However, sometimes the practice exercises felt a bit random; additionally, there was very little guidance (in this course or others) on how to handle a dataset with so many variables. Overall this was a theme throughout the specialization; we learned how to do one-off analyses/run R functions in isolation but we did not learn much in the way of how to approach end-to-end analysis on real world datasets. Additionally, as in previous courses, the course maintainers were absent - forum questions, including those about errors in the course material, have gone unanswered for multiple years.

автор: Stefanie R

21 июня 2021 г.

This course was a good way to bring together everything I learned from the previous courses, but it could have been a lot better. As with previous courses I had to teach myself a lot, particularly R code as it's simply not taught or not explained well enough. There is also no real support from moderators or course leaders - there are many posts in the discussion forums with questions or pointing out errors, some from years ago, which were never answered, so if you have a problem or don't understand something you're on your own! I also had to wait 5 weeks and get in touch with Coursera support to get my final grade, as I only got one peer review, despite submitting the assignment on time.

автор: Gonzalo C S

4 апр. 2017 г.

We spent several months waiting for this capstone to appear. The instructors dissapeared and nobody knew if this one was going finally to happen or what.

автор: Jennifer g e

22 авг. 2021 г.

Very little help to make the workshops.

автор: Alexander C

16 июля 2020 г.

LOOK OUT FOR THE START DATE