Description
Statistics with specialization R is a statistical science course using the R programming language. This language, more specifically to make statistical calculations and scientific data used during this training with a variety of modeling and statistical calculation using this language are familiar. In this tutorial, you will learn how to analyze and visualize data in R so that you can extract repeatable analysis reports from the data. You will also find a conceptual understanding of the integrated nature of statistical inference and be able to implement frequent inference and Bayesian inference.
Reviewing and critiquing statistical claims and evaluating data-driven decisions and manipulating and illustrating data using R packages are other topics of this tutorial. Also, model effective events to understand them. with the use of definitions and simple phrases instead of terms, advanced statistics are also covered in this tutorial. To help the course, you can define the knowledge, skills and tools necessary for the project, data analysis and expertise that professionals in the field of statistical data analysis, data analysis exploration to inference and modeling must acquire .
what do you learn
Bayesian statistics
Linear Regression, Bayesian Linear and Regression Analysis
Statistical inference
Programming with R and working with RStudio
Heuristic data analysis
Test statistical hypotheses
Model selection
And …
Stats specs with R specialization
Publisher: Coursera
Speaker: Çetinkaya-Rundel mine, David Banks, Colin Rundel, Merlise A Clyde
French language
Level of training: Beginner
Quantity: 5 periods
Duration of the course: with the proposed time of 3 hours per week, approximately 7 months
Course
- Introduction to probability and data with R
- Deductive statistics
- Linear regression and modeling
- Bayesian statistics
- Statistics with R Capstone
Preconditions
- Basic math, no programming experience required. A real interest in data analysis is a plus!
- You will need R and RStudio. Both are free and accessible to the public. You will need administrator access to your computer to install this software.
- In subsequent courses of the specialization, we assume knowledge and skills equivalent to those which would have been acquired in the previous courses (for example: if you decide to take course four, Bayesian Statistics, without taking the previous three courses, we suppose you have knowledge of frequentist statistics and R equivalent to what is taught in the first three courses).
Pictures
sample movie
Installation guide
After extracting with the player, your custom view.
Subtitles: English
Quality: 720p
Download link
Password file(s): ngaur.com
File size
2.68 GB