Statistical Concepts Explained and Applied in R

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[ FreeCourseWeb.com ] Udemy - Statistical Concepts Explained and Applied in R
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1. Introduction to the course
    • 1. Introduction.mp4 (48.0 MB)
    • 1. Introduction.srt (2.9 KB)
    2. Single Linear Regression
    • 1. Install R, RStudio and Basic Functionality.mp4 (43.8 MB)
    • 1. Install R, RStudio and Basic Functionality.srt (7.8 KB)
    • 10. Statistical Validity Tests.mp4 (70.4 MB)
    • 10. Statistical Validity Tests.srt (7.7 KB)
    • 11. Statistical Validity Discussion.mp4 (54.0 MB)
    • 11. Statistical Validity Discussion.srt (6.8 KB)
    • 2. Basics of Linear Regression.mp4 (27.4 MB)
    • 2. Basics of Linear Regression.srt (3.1 KB)
    • 3. Basics of Linear Regression Ctnd.mp4 (27.0 MB)
    • 3. Basics of Linear Regression Ctnd.srt (3.1 KB)
    • 4. Linear Regression Analysis.mp4 (62.6 MB)
    • 4. Linear Regression Analysis.srt (8.9 KB)
    • 5. Linear Relationships.mp4 (60.9 MB)
    • 5. Linear Relationships.srt (8.6 KB)
    • 6. Line of Best Fit, SSE and MSE.mp4 (36.4 MB)
    • 6. Line of Best Fit, SSE and MSE.srt (4.7 KB)
    • 7. Linear Regression Analysis Ctnd.mp4 (12.2 MB)
    • 7. Linear Regression Analysis Ctnd.srt (1.4 KB)
    • 8. Regression Results and Interpretation.mp4 (106.3 MB)
    • 8. Regression Results and Interpretation.srt (10.1 KB)
    • 9. Predicting Future Profits.mp4 (137.4 MB)
    • 9. Predicting Future Profits.srt (11.7 KB)
    • 3. Basics of Linear Regression Ctnd.jpeg (195.0 KB)
      • 3. Multiple Linear Regression
      • 1. Multiple Linear Regression.mp4 (54.5 MB)
      • 1. Multiple Linear Regression.srt (5.1 KB)
      • 2. Importing the data.mp4 (34.6 MB)
      • 2. Importing the data.srt (3.7 KB)
      • 3. Correlation Matrix and MLR.mp4 (74.9 MB)
      • 3. Correlation Matrix and MLR.srt (7.4 KB)
      • 4. MLR Results and ANOVA.mp4 (64.5 MB)
      • 4. MLR Results and ANOVA.srt (5.7 KB)
      • 5. The Best Model.mp4 (46.6 MB)
      • 5. The Best Model.srt (4.8 KB)
      • 6. Interaction Terms and Validity Testing.mp4 (181.9 MB)
      • 6. Interaction Terms and Validity Testing.srt (15.8 KB)
      • 7. ANOVA and Predictions.mp4 (146.5 MB)
      • 7. ANOVA and Predictions.srt (16.6 KB)
      4. Non-linear Regression
      • 1. Non-linear Regression (and Recap).mp4 (62.3 MB)
      • 1. Non-linear Regression (and Recap).srt (7.0 KB)
      • 2. Logistic Regression Overview.mp4 (194.7 MB)
      • 2. Logistic Regression Overview.srt (18.1 KB)
      • 3. Logistic Regression Odds, Logs and Poisson.mp4 (100.8 MB)
      • 3. Logistic Regression Odds, Logs and Poisson.srt (13.1 KB)
      • 4. Logistic Regression Fitting the Models in R.mp4 (198.3 MB)
      • 4. Logistic Regression Fitting the Models in R.srt (23.0 KB)
      5. Optimization Theory and Differential Calculus
      • 1. Differential Calculus - Finding the Maximum and the Minimum.mp4 (108.2 MB)
      • 1. Differential Calculus - Finding the Maximum and the Minimum.srt (14.5 KB)
      • 2. Differential Calculus One Unknown Input.mp4 (73.9 MB)
      • 2. Differential Calculus One Unknown Input.srt (8.8 KB)
      • 3. Analysis in R One Unknown Input Differential Calculus.mp4 (280.9 MB)
      • 3. Analysis in R One Unknown Input Differential Calculus.srt (27.0 KB)
      • 4. Differential Calculus - Two Unknown Inputs.mp4 (60.6 MB)
      • 4. Differential Calculus - Two Unknown Inputs.srt (6.7 KB)
      • 5. Analysis in R Two Unknown Inputs Differential Calculus.mp4 (495.5 MB)
      • 5. Analysis in R Two Unknown Inputs Differential Calculus.srt (41.6 KB)
    • Bonus Resources.txt (0.3 KB)

Description

Statistical Concepts Explained and Applied in R

Created by Lavinia Bleoca | Last updated 7/2021
Duration: 5h 16m | 5 sections | 29 lectures | Video: 1280x720, 44 KHz | 2.8 GB
Genre: eLearning | Language: English + Sub
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 analysesAccess 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 endAnyone who is serious about a job involving statistical analysesBeginner-level students interested in the correct appliances of statistical analyses from theory to completed analysis

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Statistical Concepts Explained and Applied in R

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2.8 GB
seeders:8
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Statistical Concepts Explained and Applied in R

Torrent hash: 459BA5D8446A0687AFD71AFC1069335E5C306D8A