Coursera – Statistics with R Specialization 2020-9

Description

Statistics with R specialization is a statistics course using the R programming language. This language is specifically used for statistical calculations and scientific data used in this training with a variety of modeling and statistical calculations familiar with this language. In this tutorial, you’ll learn how to analyze and visualize data in R so that you can extract reproducible analysis reports from the data. You will also gain a conceptual understanding of the integrated nature of statistical inference and be able to implement frequent inference and Bayesian inference.

Other topics covered in this tutorial include verifying and critiquing statistical claims and evaluating decisions based on data, as well as manipulating and representing data using R packages. Additionally, model effective events to understand them. Using definitions and simple sentences instead of terms, this tutorial also covers advanced statistics. To support the course, you can determine the knowledge, skills and tools required for the project, data analysis and expertise that professionals need to acquire in the field of statistical data analysis, exploration analysis to inference and modeling.

What are you learning?

Bayesian statistics
Linear regression, Bayesian linear and regression analysis
statistical inference
Programming with R and working with RStudio
Heuristic data analysis
Test statistical assumptions
Model selection
And…

Specifications of statistics with R specialization

Publisher: Coursera
Lecturers: my Cetinkaya-Rundel, David Banks, Colin Rundel, Merlise A Clyde
Language: English
Training level: beginner
Quantity: 5 periods
Duration of the course: With the suggested duration of 3 hours per week, approximately 7 months

Courses

Introduction to Probability and Data with R
Inferential statistics
Linear Regression and Modeling
Bayesian statistics
Statistics with R Capstone

requirements

Basic math skills, no programming knowledge required. A genuine interest in data analysis is an advantage!
You need R and RStudio. Both are free and publicly available. To install this software you need administrator access to your computer.
In the later courses of the specialization, we assume knowledge and skills equivalent to those acquired in the previous courses (e.g. if you choose the fourth course, Bayesian Statistics, without taking the previous three courses , we assume that you have one). Knowledge of frequentist statistics and R corresponds to what is taught in the first three courses).