Statistical Concepts Explained and Applied in R

Statistical Concepts Explained and Applied in R
Duration: 5h 16m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 2.79 GB

Genre: eLearning | Language: English [/center]

Thoroughly understand statistical concepts, apply them in R and interpret the results correctly with maximum validity

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

Requirements:
Interest in thoroughly learning statistical concepts and applying them hands-on in analyses
Access to a computer if you want to code along

Description:
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

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