Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. Furthermore, there are broad theories (frequentists, Bayesian, likelihood, design based, …) and numerous complexities (missing data, observed and unobserved confounding, biases) for performing inference. A practitioner can often be left in a debilitating maze of techniques, philosophies and nuance. This course presents the fundamentals of inference in a practical approach for getting things done. After taking this course, students will understand the broad directions of statistical inference and use this information for making informed choices in analyzing data.
Ofrecido Por
Universidad Johns HopkinsAcerca de este Curso
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Prueba Coursera para negociosQué aprenderás
Understand the process of drawing conclusions about populations or scientific truths from data
Describe variability, distributions, limits, and confidence intervals
Use p-values, confidence intervals, and permutation tests
Make informed data analysis decisions
Habilidades que obtendrás
- Statistics
- Statistical Inference
- Statistical Hypothesis Testing
¿Podría tu empresa beneficiarse de la capacitación de los empleados en las habilidades más demandadas?
Prueba Coursera para negocios
Ofrecido por
Programa - Qué aprenderás en este curso
Week 1: Probability & Expected Values
Week 2: Variability, Distribution, & Asymptotics
Week: Intervals, Testing, & Pvalues
Week 4: Power, Bootstrapping, & Permutation Tests
Reseñas
- 5 stars57,45 %
- 4 stars23,16 %
- 3 stars10,07 %
- 2 stars4,51 %
- 1 star4,78 %
Principales reseñas sobre INFERENCIA ESTADÍSTICA
In my opinion, this course is fundamental to Statistics and therefore Machine Learning. It is well explained, although it requires students to work on more mathematical aspect in parallel.
This was probably the most difficult and challenging course . Had to pull out my old stats books to remember most of it. Using R to do what we used to do with TI-83's was great!
For starters, it will demand a lot of out of class studies. It took me three months to go through the basics in Khan Academy before attempting it - and after that it was straight forward.
If you work through all the examples, you will be pleasantly surprised. This is an awesome course. Highly recommended. Many thanks to Brian Caffo for improving my understanding.
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