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Developing and Analyzing Statistical Models with R

Discover how to manipulate, analyze, and model data using R. Gain insights into data analysis, designing experiments, non-parametric tests, linear models, and advanced predictive modeling.

Intermediate

108 Lessons

23h

Certificate of Completion

Discover how to manipulate, analyze, and model data using R. Gain insights into data analysis, designing experiments, non-parametric tests, linear models, and advanced predictive modeling.

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This course includes

437 Playgrounds

9 Quizzes

Course Overview

What You'll Learn

Course Content

Apply Your Skills

Recommendations

Course Overview

R is a programming language for organizing and analyzing statistical data. R is a popular language for data mining, used for bioinformatics and statistical analysis - an essential skill in the era of big data. This course serves as a comprehensive introduction to the R programming language. You’ll learn to manipulate and analyze data working with a real-world dataset (published in Ecology in 2013). You’ll start with an introduction to data analysis before developing rich experimental designs to collect rel...Show More

R is a programming language for organizing and analyzing statistical data. R is a popular language for data mining, used for bio...Show More

What You'll Learn

Get familiarized with the basics of R via properly structured chapters and assignments.

Hands-on experience in typing along with the instructions will help overcome the "fear of the R prompt."

Learn to analyze data and think critically about data presented in research and the public realm.

Learn how to seek information to help solve problems and errors with the examples provided.

Get familiarized with the basics of R via properly structured chapters and assignments.

Course Content

Course Introduction

2 Lessons

Get familiar with practical data analysis using R, focusing on bridging theory and real-world application.

About This Course

Goals and Course Layout

Introduction to R

14 Lessons

Look at the basics of R, objects, functions, data representation, and essential data structures.

Basics of R

Objects in R

Functions in R

Data Representation in R

Vectors and Matrices in R

Data Frames and Lists in R

Summary

Exercise: Create Factors and a Data Frame

Solution: Create Factors and a Data Frame

Exercise: Create Plots with Numerical Data

Solution: Create Plots with Numerical Data

Exercise: Create Plots with Categorical Data

Solution: Create Plots with Categorical Data

Quiz: Introduction to R

Thoughts on Proper Data Analysis

4 Lessons

Examine key principles of experimental design, fair hypothesis evaluation, and selecting appropriate models in statistics.

Experimental Designs

Plan an Experiment

Decide Between Competing Analyses

Summary

Exploratory Data Analysis and Data Summarization

10 Lessons

Discover methods for data exploration, error checking, manipulation, and visualization in R using practical exercises and solutions.

About the Data

Data Exploration and Error Checking

Fixing Mistakes in the Data

Summarizing and Manipulating Data

Summary

Exercise: Hands-on Data Filtering/Manipulation

Solution: Hands-on Data Filtering/Manipulation

Exercise: Create Box and Whisker Plots

Solution: Create Box and Whisker Plots

Quiz: Exploratory Data Analysis

Introduction to Plotting

10 Lessons

Take a closer look at creating professional and customizable data visualizations in R.

Introduction to Plotting

Different Types of Plotting Techniques

Plotting Data Using gplots

Plotting Data Using ggplot2

Summary

Exercise: Create Plots with Facets, Colors and Descriptive Labels

Solution: Create Plots with Facets, Colors and Descriptive Labels

Exercise: Create Enhanced Bar Plots

Solution: Create Enhanced Bar Plots

Quiz: Introduction to Plotting

Basic Statistical Analysis Using R

11 Lessons

Simplify complex topics in statistical analysis with R, including normality testing, linear models, and nonparametric tests.

Basic Statistical Analysis

Testing for Normality in Our Data

Nonparametric Tests

Introducing Linear Models

Multiple Comparisons

Summary

Exercise: Conduct a Series of One-way ANOVAs

Solution: Conduct a Series of One-way ANOVAs

Exercise: Examine the Effects of Log-transformation on Results

Solution: Examine the Effects of Log-transformation on Results

Quiz: Basic Statistical Analysis Using R

More Linear Models in R

15 Lessons

Master the steps to analyze linear models, perform ANOVA/ANCOVA, and visualize results in R.

Introduction to Multi-way ANOVA

More Linear Models

Linear Regression

Plotting the Regression

Analysis of Covariance (ANCOVA)

The Predict() Function

Plotting with ggplot() Instead of qplot()

Summary

Exercise: Analyze Data with Multiple Predictors

Solution: Analyze Data with Multiple Predictors

Exercise: Perform Analysis of Covariance (ANCOVA) and Plot

Solution: Perform Analysis of Covariance (ANCOVA) and Plot

Exercise: Statistical Analysis with Different Interactions

Solution: Statistical Analysis with Different Interactions

Quiz: More Linear Models

Advanced Statistical Analysis Using R

9 Lessons

Step through advanced statistical models in R to analyze non-normal data and visualize results.

Generalized Linear Models

Understanding and Interpreting the GLM

GLMs and ANCOVAs

Summary

Exercise: Explore the Data with Multiple Predictors

Solution: Explore Data with Multiple Predictors

Exercise: Appropriately Visualize the Significant Findings

Solution: Appropriately Visualize the Significant Findings

Quiz: Advanced Analytical Statistics Using R

Mixed-effects Model

10 Lessons

Get started with developing mixed-effects models in R, diagnostics, model selection, and analysis.

Understanding Mixed-effects Models

Diagnostic Plots

Generalized Linear Mixed Model (GLMM)

More About Model Selection

Summary

Exercise: Rerun the ANCOVA Models

Solution: Rerun the ANCOVA Models

Exercise: Compare the AIC Scores

Solution: Compare the AIC Scores

Quiz: Mixed Effects Models

10.

Advanced Data Wrangling and Plotting

11 Lessons

Work your way through advanced data manipulation and visualization techniques using the tidyverse and ggplot2.

The tidyverse Library

Basic Data Wrangling

Advanced Data Wrangling

Making Better Figures with ggplot2

Customizing a Figure in R

Faceting in R

Combining Data Wrangling and Plotting with ggplot2

Summary

Exercise: Create a Bar Graph for Each Tank in the Experiment

Solution: Create a Bar Graph for Each Tank in the Experiment

Quiz: Advanced Wrangling and Plotting

11.

Writing Loops and Functions in R

8 Lessons

Enhance your skills in writing loops and functions in R to streamline data analysis.

For Loops

Functions

Writing a Simple Function

Writing More Complex Functions

Summary

Exercise: Automate the Repeated Tasks and Simulate the Data

Solution: Automate the Repeated Tasks and Simulate the Data

Quiz: Writing Loops and Functions in R

12.

Appendix

2 Lessons

Get started with R setup, enhance coding with RStudio, and emphasize annotated code for clarity.

Setup on the Local Machine

Create Well-documented and Annotated Code

13.

Conclusion

2 Lessons

Focus on the importance of understanding data and creating effective figures.

Final Thoughts

Course Author

Oxford University Press

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