Statistical Concepts Explained and Applied in R
- Description
- Curriculum
- FAQ
- Reviews
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!
-
3Install R, RStudio and Basic FunctionalityVideo lesson
-
4Basics of Linear RegressionVideo lesson
-
5Basics of Linear Regression CtndVideo lesson
-
6Linear Regression AnalysisVideo lesson
-
7Linear RelationshipsVideo lesson
-
8Line of Best Fit, SSE and MSEVideo lesson
-
9Linear Regression Analysis CtndVideo lesson
-
10Regression Results and InterpretationVideo lesson
-
11Predicting Future ProfitsVideo lesson
-
12Statistical Validity TestsVideo lesson
-
13Statistical Validity DiscussionVideo lesson
-
14Single Linear RegressionQuiz
Test what you know about single linear regression

External Links May Contain Affiliate Links read more