Performing Modern Statistical Analysis with R

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Intermediate

111 Lessons

29h 55min

Certificate of Completion

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This course includes

229 Playgrounds

15 Quizzes

This course includes

229 Playgrounds

15 Quizzes

Course Overview

R is a widely used programming language for statistical computing. It features robust libraries that cover everything from basic data analytics to visualization functions for presentation. R is used by professional data scientists, researchers, and marketers. This course is a comprehensive introduction to modern statistical analysis using R, particularly for researchers in life and environmental sciences. You’ll review R and cover its functionality with its various packages. You'll review essential statist...Show More

What You'll Learn

The ability to perform basic and advanced statistical analysis with R

Working knowledge of various R packages and commands

An understanding of the contemporary framework for interpreting statistical models in R

The ability to test model prediction using diagnostic plots in R

An understanding of retrieving, cleaning, analyzing, and visualizing data with R

A deep understanding of generalized linear models for data with non-normal distributions

What You'll Learn

The ability to perform basic and advanced statistical analysis with R

Course Content

Introduction

About the Course

Getting Started

Motivation for Statistical Analysis

The R Programming Language and its Packages

Description

The Pollination Data Summarizing the Data Describing the Data Comparing Groups The Reproducibility Crisis and R Scripts Quiz: Description Summary

Estimation

Estimation with the Pollination Data Standard Deviations and Standard Errors The Normal Distribution and the Central Limit Theorem Quiz: Estimation Summary

Linear Models

Introduction to Linear Model Analysis Standard Error of the Difference Confidence Intervals and Darwin’s Question Releveling to Calculate Mean and Standard Error Normality and Equal Variance Challenge: Summary Statistics and Plotting in R Solution: Summary Statistics and Plotting in R Quiz: Linear Models Summary

Regression

Introduction to Linear Regression The Janka Hardness Data Correlation and Linear Regression in R Assumptions in Linear Regression Quiz: Regression Summary

Prediction

6 Lessons

Testing

7 Lessons

Intervals

10 Lessons

Analysis of Variance

6 Lessons

10.

Factorial Designs

8 Lessons

11.

Analysis of Covariance

6 Lessons

12.

Linear Model Complexities

9 Lessons

13.

Generalized Linear Models

7 Lessons

14.

GLMs for Count Data

4 Lessons

15.

Binomial GLMs

5 Lessons

16.

GLMs for Binary Data

5 Lessons

17.

Conclusion

5 Lessons

18.

Appendix

2 Lessons

Course Author

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Anthony Walker

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Evan Dunbar

ML Engineer

Carlos Matias La Borde

Software Developer

Souvik Kundu

Front-end Developer

Vinay Krishnaiah

Software Developer

Eric Downs

Musician/Entrepeneur

Kenan Eyvazov

DevOps Engineer

Souvik Kundu

Front-end Developer

Eric Downs

Musician/Entrepeneur

Anthony Walker

@_webarchitect_

Evan Dunbar

ML Engineer

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