Data-Centric Statistical Inference Using R and Tidyverse

This course provides a practical guide using R and the tidyverse, guiding statistical concepts and analysis techniques.

Beginner

99 Lessons

17h

Certificate of Completion

This course provides a practical guide using R and the tidyverse, guiding statistical concepts and analysis techniques.

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

311 Playgrounds

10 Quizzes

This course includes

311 Playgrounds

10 Quizzes

Course Overview

The world is full of data and it can be quite challenging to infer the knowledge based on statistical reasoning. This course aims to equip you with the skills you need to play with your data, wrangle it, and visualize it. Starting with data visualization, the course gets learners building ggplot2 graphs early on and then continues to reinforce important concepts graphically throughout the course. After moving through data wrangling and data importing, you’ll be introduced to modeling, which plays a promi...Show More

What You'll Learn

Working knowledge of R, ModernDive, and tidyverse to process data

Hands-on experience of data preprocessing, wrangling, and visualization

The ability to apply data-centric concepts for regression analysis, sampling, confidence intervals, and hypothesis testing and interpretation

The ability to tell a story using data of different case studies

The ability to infer insights and conclusions from data using different packages

What You'll Learn

Working knowledge of R, ModernDive, and tidyverse to process data

Course Content

Getting Started with Data in R

Getting Started

How Do We Code in R?Tips on Learning to Code Explore Our First Dataset Exploring Data Frames Test Your Skills on Getting Started with Data in R

Data Visualization

The Grammar of Graphics

Scatterplots Overplotting Line Graphs Histograms Facets Boxplots Barplots When to Avoid Pie Charts Recap: Data Visualization Test Your Skills on Data Visualization

Data Wrangling

The Pipe Operator Filter Rows Summarize Variables Group by Rows Mutate Existing Variables Join Data Frames Other Verbs Recap: Data Wrangling Test Your Skills on Data Wrangling

Data Importing and “Tidy” Data

Introduction of Data and Needed Packages Tidy Data Converting to Tidy Data Case Study: Democracy in Guatemala Tidyverse Package Test Your Skills on Data Importing and Tidy Data

Basic Regression

Introduction and Needed Packages One Numerical Explanatory Variable EDA for a Numerical Explanatory Variable Simple Linear Regression for a Numerical Explanatory Variable Observed/Fitted Values and Residuals on Numerical Variables One Categorical Explanatory Variable Exploratory Data Analysis of One Categorical Explanatory Variable Linear Regression for One Categorical Explanatory Variable Observed/Fitted Values and Residuals on Categorical Variables Correlation Is Not Necessarily Causation The Best-Fitting Line The get_regression_x() Functions Test Your Skills on Basic Regression

Multiple Regression

9 Lessons

Statistical Inference with the infer Package

8 Lessons

Bootstrapping and Confidence Intervals

13 Lessons

Hypothesis Testing

9 Lessons

Inference for Regression

9 Lessons

Tell a Story with Data

4 Lessons

Appendix

2 Lessons

Course Author

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Emma Bostian 🐞

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