This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data
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Habilidades que obtendrás
- 5 stars83,12 %
- 4 stars13,30 %
- 3 stars1,94 %
- 2 stars0,63 %
- 1 star0,99 %
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Excellent course and specialization. I have learnt a lot. Could you also add generalize linear regressoin including logistic, poisson, negative bionomial and survival analysis. Thanks,
This was hard; The Statistics part became harder and harder and the R part seemed to not keep up with it. You need to learn more R on your own, which is a challenge - there are man
The course is very well explained I had to refer other materials for ANOVA technique to understand it better hence that part can be either improved OR more reference material be provided
Great course. If you put in a little effort, you will come out with a lot of new knowledge. I recommend using the book after you have seen the movies. It gives a deeper picture of how it works. Great!
¿Cuándo podré acceder a las lecciones y tareas?
¿Qué recibiré si me suscribo a este Programa especializado?
¿Hay ayuda económica disponible?
Cost of the Course
Can I just enroll in a single course? I'm not interested in the entire Specialization.
Will I receive a transcript from Duke University for completing this course?
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