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Comentários e feedback de alunos de Statistics with R Capstone da instituição Universidade Duke

207 classificações
51 avaliações

Sobre o curso

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....

Melhores avaliações

23 de Mar de 2017

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.

12 de Jul de 2017

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.

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26 — 50 de 50 Avaliações para o Statistics with R Capstone

por Andrea P

8 de Out de 2019

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

por Andy D

3 de Abr de 2017

The Capstone project really helped tie the program together

por Lou B V

10 de Out de 2020

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

por Marco G

13 de Jan de 2021

Great project, real life application.

por Arjun B

22 de Fev de 2018

Strong Capstone Project

por Gabriel T F

17 de Ago de 2020

A very good course

por Marina Z

1 de Ago de 2017

Great! Enjoyed it!

por Jim F

6 de Abr de 2018

Loved this course

por Roland

2 de Fev de 2018

Excellent course

por José M C

22 de Mar de 2017

Great activity!!

por Oscar C R

5 de Dez de 2020

Good Course

por Vinh H

12 de Out de 2017

Very good !

por Albert C G

1 de Jul de 2017


por PAUL M

10 de Jul de 2018


por Bruce H

6 de Dez de 2017

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.

por Mariia D

22 de Mar de 2021

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

por Benjamin E

12 de Jul de 2020

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.

por Matthew C

3 de Set de 2020

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

por ninad p

7 de Dez de 2019

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

por Tom M

15 de Ago de 2017


por Katy S

1 de Fev de 2021

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.

por Stefanie R

21 de Jun de 2021

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.

por Gonzalo C S

4 de Abr de 2017

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.

por Jennifer g e

22 de Ago de 2021

Very little help to make the workshops.

por Alexander C

16 de Jul de 2020