Hands-on learning with R: Analyze, visualize, and interpret real world data like a pro.
What you will learn
What is R?
History and applications of R
Installing and Configuring R and RStudio
Basic R Syntax and Data Types
Vectors, Matrices, and Arrays
Data Frames and Lists
Conditional Statements (if-else)
Loops (for, while)
Creating and Using Functions in R
Function Arguments and Scoping
Data Manipulation with dplyr (filter, select, mutate, arrange)
Data Tidying with Tidyr (pivot_longer, pivot_wider)
Joining and Merging Data Frames
Creating Various Types of Plots (scatter plots, bar plots, line plots, histograms)
Customizing Plot Aesthetics (colors, labels, themes)
Creating Interactive Plots
Descriptive Statistics (mean, median, standard deviation, quartiles)
Hypothesis Testing (t-tests, chi-squared tests)
Regression Analysis (linear regression, multiple regression)
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- Master the art of data storytelling, transforming raw information into compelling narratives that drive decision-making.
- Develop a robust R toolkit by actively engaging with practical coding challenges and debugging common errors.
- Gain proficiency in data wrangling, efficiently cleaning and structuring messy datasets for analysis.
- Unlock the power of visualization to reveal hidden patterns and communicate complex findings with clarity and impact.
- Build a portfolio of real-world projects that showcase your R capabilities to potential employers and collaborators.
- Understand the underlying principles of statistical inference, enabling you to draw meaningful conclusions from your data.
- Implement predictive modeling techniques to forecast trends and make informed recommendations.
- Learn to integrate R with other data sources and tools for a more comprehensive analytical workflow.
- Develop best practices for reproducible research, ensuring your analyses are transparent and verifiable.
- Cultivate a problem-solving mindset for tackling diverse data challenges across various domains.
- Enhance your analytical agility by learning to adapt R techniques to new and evolving data scenarios.
- Discover how to interpret model outputs and translate statistical results into actionable business insights.
- Gain confidence in presenting data-driven arguments backed by sound statistical evidence.
- Become an efficient R user, streamlining your coding process and maximizing productivity.
- Explore advanced data manipulation and analysis strategies beyond the fundamental operations.
- PRO: Emphasis on practical application ensures immediate transferability of skills to real-world scenarios.
- PRO: Exposure to industry-standard libraries prepares you for common data analysis tasks.
- PRO: Hands-on project-based learning fosters deeper understanding and retention.
- CON: May require prior basic programming familiarity for optimal benefit, though not strictly mandatory.
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