Learn how to model data, its statistical analysis, and visualization in R.

Statistical Analysis with R

R is a popular language for data mining, and is used for bioinformatics and statistical analysis—an essential skill in the era of big data.

This module serves as a comprehensive introduction to the R programming language. We’ll learn to manipulate and analyze data, working with a real-world dataset (published in Ecology in 2013). We’ll start with an introduction to data analysis, before developing rich experimental designs to collect reliable data. Then, we’ll plot our data using R and continue with fundamental statistical analysis. Moreover, we’ll build our understanding of the data with more advanced analyses, using R to perform non-parametric tests and linear models. Finally, we’ll explore advanced data wrangling and predictive modeling.

This module will progress from linear modeling to mixed-effects analyses. By the end, we’ll be able to write advanced functions in R for any dataset.

Developing and Analyzing Statistical Models with R

## Assignment

Make a bar plot as we did in the [Exercise: Create Plots with Facets, Colors, and Descriptive Labels](https://www.educative.io/courses/developing-analyzing-statistical-models-r/exercise-create-plots-with-facets-colors-and-descriptive-labels),  but instead of using the initial `SVL` data, make it from the following:


- Use the final metamorph `Mass` data (`Mass. final`).
- Have it grouped by predator treatment (`Pred`) and hatching age (`Hatch`).

Make sure it has correct error bars, and give it some creative colors! Before starting, please think about what existing code we have in our code space that we can modify to make this figure.

> **Tip:** Press the “Show Hint” button to get the code mentioned above.

# Assignment

Make a bar plot as we did in the [Exercise: Create Plots with Facets, Colors, and Descriptive Labels](https://www.educative.io/courses/developing-analyzing-statistical-models-r/exercise-create-plots-with-facets-colors-and-descriptive-labels),  but instead of using the initial `SVL` data, make it from the following:


- Use the final metamorph `Mass` data (`Mass. final`).
- Have it grouped by predator treatment (`Pred`) and hatching age (`Hatch`).

Make sure it has correct error bars, and give it some creative colors! Before starting, please think about what existing code we have in our code space that we can modify to make this figure.

> **Tip:** Press the “Show Hint” button to get the code mentioned above.

Use what we’ve learned so far to make a bar plot with colors and additional informative axis labels.

Introduction to R

Thoughts on Proper Data Analysis

Exploratory Data Analysis and Data Summarization

Introduction to Plotting

Basic Statistical Analysis Using R

More Linear Models in R

Advanced Statistical Analysis Using R

Mixed-effects Model

Advanced Data Wrangling and Plotting

Writing Loops and Functions in R

Appendix

Conclusion

Exercise: Create Enhanced Bar Plots

Assignment