Statistical Concepts Explained and Applied in R
What you'll learn
- Thorough understanding of basic and advanced statistical theory
- How to perform simple and advanced statistical analyses in R
- How to fully and correctly interpret the results
- How to correctly present the results in papers or reports
- How to get reproducible results with every type of analysis carried out in the course
- How to make accurate predictions based on your regression results
- How to deal with real issues in statistical modeling
- The concepts are made simple and the understanding about them is at an advanced level once you finish the course
- Interest in thoroughly learning statistical concepts and applying them hands-on in analyses
- Access to a computer if you want to code along
This course takes you from basic statistics and linear regression into more advanced concepts, such as multivariate regression, anovas, logistic and time analyses. It offers extensive examples of application in R and complete guidance of statistical validity, as required for in academic papers or while working as a statistician.
Statistical models need to fulfill many requirements and need to pass several tests, and these make up an important part of the lectures.
This course shows you how to understand, interpret, perform and validate most common regressions, from theory and concept to finished (gradable) paper/report by guiding you through all mandatory steps and associated tests.
Taught by a university lecturer in Econometrics and Math, with several international statistical journal publications and a Ph.D. in Economics, you are offered the best route to success, either in academia or in the business world.
The course contents focus on theory, data and analysis, while triangulating important theorems and tests of validity into ensuring robust results and reproducible analyses. Start learning today for a brighter future!
Who this course is for:
- Undergraduate/graduate/academic scholars/managers who wish to perform a statistical analysis from beginning to end
- Anyone who is serious about a job involving statistical analyses
- Beginner-level students interested in the correct appliances of statistical analyses from theory to completed analysis
* PhD in Economics, MBA and a BoS in Computer and Information Science
* Data analyst and statistician (I especially love R). I have published several academic articles with advanced non-linear quantitative and qualitative data analyses/data mining (please see publications section on my LinkedIn). Azure Certified in Data Analysis and Artificial Intelligence/Machine Learning.
* University lecturer in Managerial Economics and Math, as well as teacher in Science and Technology
* Web developer with 6 years of working experience (full-stack OOP PHP LAMP development), experienced server and network administrator, photographer and media production. Azure Certified in C# software development.
* I am here to share my knowledge with those willing to learn, and to improve through teaching others by doing :)
* Welcome to my courses and feel free to leave a comment if you have special requests about something that's not included, but you would like to learn about