Statistical Concepts Explained and Applied in R

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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 the 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 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 the completed analysis
  • Last updated 8/2021

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Statistical Concepts Explained and Applied in R Thoroughly understand statistical concepts, apply them in R and interpret the results correctly with a maximum validity

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